Digital Electronic MCQ Set 1
1. Assume that an image f(x, y) is sampled so that the result has M rows and N columns. If the values of the coordinates at the origin are (x, y) = (0, 0), then the notation (0, 1) is used to signify :
a) Second sample along first row
b) First sample along second row
c) First sample along first row
d) Second sample along second row
Answer
Answer: a [Reason:] The values of the coordinates at the origin are (x, y) = (0, 0). Then, the next coordinate values (second sample) along the first row of the image are represented as (x, y) = (0, 1).
2. The resulting image of sampling and quantization is considered a matrix of real numbers. By what name(s) the element of this matrix array is called ____
a) Image element or Picture element
b) Pixel or Pel
c) All of the mentioned
d) None of the mentioned
Answer
Answer: c [Reason:] Sampling and Quantization of an image f(x, y) forms a matrix of real numbers and each element of this matrix array is commonly known as Image element or Picture element or Pixel or Pel.
3. Let Z be the set of real integers and R the set of real numbers. The sampling process may be viewed as partitioning the x-y plane into a grid, with the central coordinates of each grid being from the Cartesian product Z2, that is a set of all ordered pairs (zi, zj), with zi and zj being integers from Z. Then, f(x, y) is said a digital image if:
a) (x, y) are integers from Z2 and f is a function that assigns a gray-level value (from Z) to each distinct pair of coordinates (x, y)
b) (x, y) are integers from R2 and f is a function that assigns a gray-level value (from R) to each distinct pair of coordinates (x, y)
c) (x, y) are integers from R2 and f is a function that assigns a gray-level value (from Z) to each distinct pair of coordinates (x, y)
d) (x, y) are integers from Z2 and f is a function that assigns a gray-level value (from R) to each distinct pair of coordinates (x, y)
Answer
Answer: d [Reason:] In the given condition, f(x, y) is a digital image if (x, y) are integers from Z2 and f a function that assigns a gray-level value (that is, a real number from the set R) to each distinct coordinate pair (x, y).
4. Let Z be the set of real integers and R the set of real numbers. The sampling process may be viewed as partitioning the x-y plane into a grid, with the central coordinates of each grid being from the Cartesian product Z2, that is a set of all ordered pairs (zi, zj), with zi and zj being integers from Z. Then, f(x, y) is a digital image if (x, y) are integers from Z2 and f is a function that assigns a gray-level value (that is, a real number from the set R) to each distinct coordinate pair (x, y). What happens to the digital image if the gray levels also are integers?
a) The Digital image then becomes a 2-D function whose coordinates and amplitude values are integers
b) The Digital image then becomes a 1-D function whose coordinates and amplitude values are integers
c) The gray level can never be integer
d) None of the mentioned
Answer
Answer: a [Reason:] In Quantization Process if the gray levels also are integers the Digital image then becomes a 2-D function whose coordinates and amplitude values are integers.
5. The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of gray levels allowed for each pixel. The value M and N have to be:
a) M and N have to be positive integer
b) M and N have to be negative integer
c) M have to be negative and N have to be positive integer
d) M have to be positive and N have to be negative integer
Answer
Answer: a [Reason:] The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of max gray level. There are no requirements on M and N, other than that M and N have to be positive integer.
6. The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of max gray levels. There are no requirements on M and N, other than that M and N have to be positive integer. However, the number of gray levels typically is
a) An integer power of 2 i.e. L = 2k
b) A Real power of 2 i.e. L = 2k
c) Two times the integer value i.e. L = 2k
d) None of the mentioned
Answer
Answer: a [Reason:] Due to processing, storage, and considering the sampling hardware, the number of gray levels typically is an integer power of 2 i.e. L = 2k.
7. The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of max gray levels is an integer power of 2 i.e. L = 2k, allowed for each pixel. If we assume that the discrete levels are equally spaced and that they are integers then they are in the interval ____ and Sometimes the range of values spanned by the gray scale is called the ________ of an image.
a) [0, L – 1] and static range respectively
b) [0, L / 2] and dynamic range respectively
c) [0, L / 2] and static range respectively
d) [0, L – 1] and dynamic range respectively
Answer
Answer: d [Reason:] In digitization process M rows and N columns have to be positive and for the number, L, of discrete gray levels typically an integer power of 2 for each pixel. If we assume that the discrete levels are equally spaced and that they are integers then they lie in the interval [0, L-1] and Sometimes the range of values spanned by the gray scale is called the dynamic range of an image.
8. After digitization process a digital image with M rows and N columns have to be positive and for the number, L, max gray levels i.e. an integer power of 2 for each pixel. Then, the number b, of bits required to store a digitized image is:
a) b=M*N*k
b) b=M*N*L
c) b=M*L*k
d) b=L*N*k
Answer
Answer: a [Reason:] In digital image of M rows and N columns and L max gray levels an integer power of 2 for each pixel. The number, b, of bits required to store a digitized image is: b=M*N*k.
9. An image whose gray-levels span a significant portion of gray scale have ____ dynamic range while an image with dull, washed out gray look have ____ dynamic range.
a) Low and High respectively
b) High and Low respectively
c) Both have High dynamic range, irrespective of gray levels span significance on gray scale
d) Both have Low dynamic range, irrespective of gray levels span significance on gray scale
Answer
Answer: b [Reason:] An image whose gray-levels signifies a large portion of gray scale have High dynamic range, while that with dull, washed out gray look have Low dynamic range.
10. Validate the statement “When in an Image an appreciable number of pixels exhibit high dynamic range, the image will have high contrast.”
a) True
b) False
Answer
Answer: a [Reason:] In an Image if an appreciable number of pixels exhibit high dynamic range property, the image will have high contrast.
11. In digital image of M rows and N columns and L discrete gray levels, calculate the bits required to store a digitized image for M=N=32 and L=16.
a) 16384
b) 4096
c) 8192
d) 512
Answer
Answer: b [Reason:] In digital image of M rows and N columns and L max gray levels i.e. an integer power of 2 for each pixel. The number, b, of bits required to store a digitized image is: b=M*N*k.
For L=16, k=4.
i.e. b=4096.
Digital Electronic MCQ Set 2
1. A filter is applied to an image whose response is independent of the direction of discontinuities in the image. The filter is/are ________
a) Isotropic filters
b) Box filters
c) Median filter
d) All of the mentioned
Answer
Answer: a [Reason:] Isotropic filter are rotation invariant because it has a same response when applied to the image first and the after rotating the image.
2. In isotropic filtering, which of the following is/are the simplest isotropic derivative operator?
a) Laplacian
b) Gradient
c) All of the mentioned
d) None of the mentioned
Answer
Answer: a [Reason:] An isotropic filtering is an example of second order derivative for enhancement and uses Laplacian as the simplest derivative operator, while gradient is used with first derivatives.
3. The Laplacian is which of the following operator?
a) Nonlinear operator
b) Order-Statistic operator
c) Linear operator
d) None of the mentioned
Answer
Answer: c [Reason:] Derivative of any order are linear operations and since, Laplacian is the simplest isotropic derivative operator, so is a linear operator.
Order-Statistics operator are nonlinear operators.
4. A Laplacian for an image f(x, y) is defined as: 
is given by ________
a) [f(x + 1, y) + f(x – 1, y) – 2f(x, y)] and [f(x, y + 1) + f(x, y – 1) – 2f(x, y)] respectively
b) [f(x + 1, y + 1) + f(x, y – 1) – 2f(x, y)] and [f(x , y + 1) + f(x – 1, y) – 2f(x, y)] respectively
c) [f(x, y + 1) + f(x, y – 1) – 2f(x, y)] and [f(x + 1, y) + f(x – 1, y) – 2f(x, y)] respectively
d) None of the mentioned
Answer
Answer: a [Reason:] For a Laplacian given by:∇2 f=
Applying second order derivative in x direction (∂2 f)/∂x2 = [f(x + 1, y) + f(x – 1, y) – 2f(x, y)], and
Applying second order derivative in y direction (∂2 f)/∂y2 = [f(x, y + 1) + f(x, y – 1) – 2f(x, y)].
5. The Laplacian ∇2 f=[f(x + 1, y) + f(x – 1, y) + f(x, y + 1) + f(x, y – 1) – 4f(x, y)], gives an isotropic result for rotations in increment by what degree?
a) 90o
b) 0o
c) 45o
d) None of the mentioned
Answer
Answer: a [Reason:] The given Laplacian gives isotropic result for 90o incremental rotations.
6. The Laplacian incorporated with diagonal directions, i.e. ∇2 f=[f(x + 1, y) + f(x – 1, y) + f(x, y + 1) + f(x, y – 1) – 8f(x, y)], gives an isotropic result for rotations in increment by what degree?
a) 90o
b) 0o
c) 45o
d) None of the mentioned
Answer
Answer: a [Reason:] The given Laplacian since includes the diagonal direction, so, gives an isotropic result for 45o incremental rotations.
7. Applying Laplacian has which of the following result(s)?
a) Produces image having greyish edge lines
b) Produces image having featureless background
c) All of the mentioned
d) None of the mentioned
Answer
Answer: c [Reason:] Since, Laplacian is a derivative operator, so, highlights the gray-level discontinuities in an image and deemphasizes areas with slowly varying gray levels. Hence, produces images having greyish edge lines superimposed on featureless background.
8. Applying Laplacian produces image having featureless background which is recovered maintaining the sharpness of Laplacian operation by either adding or subtracting it from the original image depending upon the Laplacian definition used. Which of the following is true based on above statement?
a) If definition used has a negative center coefficient, then subtraction is done
b) If definition used has a positive center coefficient, then subtraction is done
c) If definition used has a negative center coefficient, then addition is done
d) None of the mentioned
Answer
Answer: a [Reason:] Applying Laplacian produces image having featureless background which is recovered maintaining the sharpness of Laplacian operation using original image either added if Laplacian definition used has a positive center coefficient or subtracting result from original image if has a negative center coefficient.
9. A mask of size 3*3 is formed using Laplacian including diagonal neighbors that has central coefficient as 9. Then, what would be the central coefficient of same mask if it is made without diagonal neighbors?
a) 5
b) -5
c) 8
d) -8
Answer
Answer: a [Reason:] The mask formed by eliminating diagonal neighbors i.e. 4f(x, y), since each diagonal contain a -2f(x, y), the mask has 5 as its central coefficient.
10. Which of the following mask(s) is/are used to sharpen images by subtracting a blurred version of original image from the original image itself?
a) Unsharp mask
b) High-boost filter
c) All of the mentioned
d) None of the mentioned
Answer
Answer: c [Reason:] Unsharp mask sharpens images by subtracting a blurred version of original image from the original image itself.
A high-boost filter is a generalized form of unsharp mask.
11. Which of the following gives an expression for high boost filtered image fhb, if f represents an image, f blurred version of f, fs unsharp mask filtered image and A ≥ 1?
a) fhb = (A – 1) f(x, y) + f(x, y) – f x, y)
b) fhb = A f(x, y) – f(x,y)
c) fhb = (A – 1) f(x, y) + fs(x, y)
d) All of the mentioned
Answer
Answer: d [Reason:] A high-boost filter is a generalized form of unsharp mask and is given by:
fhb = A f(x, y) – f (x, y)
Or, fhb = (A – 1) f(x, y) + f(x, y) – f(x, y), that can be written as
fhb = (A – 1) f(x, y) + fs(x, y), where fs(x, y) = f(x, y) – f (x, y).
12. If we use a Laplacian to obtain sharp image for unsharp mask filtered image fs(x, y) of f(x, y) as input image, and if the center coefficient of the Laplacian mask is negative then, which of the following expression gives the high boost filtered image fhb, if ∇2 f represent Laplacian?
a) fhb = A f(x, y) – ∇2 f(x,y)
b) fhb = A f(x, y) + ∇2 f(x,y)
c) fhb = ∇2 f(x,y)
d) None of the mentioned
Answer
Answer: a [Reason:] If Laplacian is used to obtain sharp image for unsharp mask filtered image, then
.
13. If for an input image f(x, y) and the ∇2 f represents Laplacian, then if, high boost filtered image is given by
.
For what value of A this high boost filtering becomes the standard Laplacian sharpening filter?
a) 0
b) 1
c) -1
d) ∞
Answer
Answer: b [Reason:] for A=1 the high boost filtering is given by:
.
Digital Electronic MCQ Set 3
1. Which of the following is the primary objective of sharpening of an image?
a) Blurring the image
b) Highlight fine details in the image
c) Increase the brightness of the image
d) Decrease the brightness of the image
Answer
Answer: b [Reason:] The sharpening of image helps in highlighting the fine details that are present in the image or to enhance the details that are blurred due to some reason like adding noise.
2. Image sharpening process is used in electronic printing.
a) True
b) False
Answer
Answer: a [Reason:] The applications of image sharpening is present in various fields like electronic printing, autonomous guidance in military systems, medical imaging and industrial inspection.
3. In spatial domain, which of the following operation is done on the pixels in sharpening the image?
a) Integration
b) Average
c) Median
d) Differentiation
Answer
Answer: d [Reason:] We know that, in blurring the image, we perform the average of pixels which can be considered as integration. As sharpening is the opposite process of blurring, logically we can tell that we perform differentiation on the pixels to sharpen the image.
4. Image differentiation enhances the edges, discontinuities and deemphasizes the pixels with slow varying gray levels.
a) True
b) False
Answer
Answer: a [Reason:] Fundamentally, the strength of the response of the derivative operative is proportional to the degree of discontinuity in the image. So, we can state that image differentiation enhances the edges, discontinuities and deemphasizes the pixels with slow varying gray levels.
5. In which of the following cases, we wouldn’t worry about the behaviour of sharpening filter?
a) Flat segments
b) Step discontinuities
c) Ramp discontinuities
d) Slow varying gray values
Answer
Answer: d [Reason:] We are interested in the behaviour of derivatives used in sharpening in the constant gray level areas i.e., flat segments, and at the onset and end of discontinuities, i.e., step and ramp discontinuities.
6. Which of the following is the valid response when we apply a first derivative?
a) Non-zero at flat segments
b) Zero at the onset of gray level step
c) Zero in flat segments
d) Zero along ramps
Answer
Answer: c [Reason:] The derivations of digital functions are defined in terms of differences. The definition we use for first derivative should be zero in flat segments, nonzero at the onset of a gray level step or ramp and nonzero along the ramps.
7. Which of the following is not a valid response when we apply a second derivative?
a) Zero response at onset of gray level step
b) Nonzero response at onset of gray level step
c) Zero response at flat segments
d) Nonzero response along the ramps
Answer
Answer: b [Reason:] The derivations of digital functions are defined in terms of differences. The definition we use for second derivative should be zero in flat segments, zero at the onset of a gray level step or ramp and nonzero along the ramps.
8. If f(x,y) is an image function of two variables, then the first order derivative of a one dimensional function, f(x) is:
a) f(x+1)-f(x)
b) f(x)-f(x+1)
c) f(x-1)-f(x+1)
d) f(x)+f(x-1)
Answer
Answer: a [Reason:] The first order derivative of a single dimensional function f(x) is the difference between f(x) and f(x+1).
That is, ∂f/∂x=f(x+1)-f(x).
9. Isolated point is also called as noise point.
a) True
b) False
Answer
Answer: a [Reason:] The point which has very high or very low gray level value compared to its neighbours, then that point is called as isolated point or noise point. The noise point of is of one pixel size.
10. What is the thickness of the edges produced by first order derivatives when compared to that of second order derivatives?
a) Finer
b) Equal
c) Thicker
d) Independent
Answer
Answer: c [Reason:] We know that, the first order derivative is nonzero along the entire ramp while the second order is zero along the ramp. So, we can conclude that the first order derivatives produce thicker edges and the second order derivatives produce much finer edges.
11. First order derivative can enhance the fine detail in the image compared to that of second order derivative.
a) True
b) False
Answer
Answer: b [Reason:] The response at and around the noise point is much stronger for the second order derivative than for the first order derivative. So, we can state that the second order derivative is better to enhance the fine details in the image including noise when compared to that of first order derivative.
12. Which of the following derivatives produce a double response at step changes in gray level?
a) First order derivative
b) Third order derivative
c) Second order derivative
d) First and second order derivatives
Answer
Answer: c [Reason:] Second order derivatives produce a double line response for the step changes in the gray level. We also note of second-order derivatives that, for similar changes in gray-level values in an image, their response is stronger to a line than to a step, and to a point than to a line.
Digital Electronic MCQ Set 4
1. Noise reduction is obtained by blurring the image using smoothing filter.
a) True
b) False
Answer
Answer: a [Reason:] Noise reduction is obtained by blurring the image using smoothing filter. Blurring is used in pre-processing steps, such as removal of small details from an image prior to object extraction and, bridging of small gaps in lines or curves.
2. What is the output of a smoothing, linear spatial filter?
a) Median of pixels
b) Maximum of pixels
c) Minimum of pixels
d) Average of pixels
Answer
Answer: d [Reason:] The output or response of a smoothing, linear spatial filter is simply the average of the pixels contained in the neighbourhood of the filter mask.
3. Smoothing linear filter is also known as median filter.
a) True
b) False
Answer
Answer: b [Reason:] Since the smoothing spatial filter performs the average of the pixels, it is also called as averaging filter.
4. Which of the following in an image can be removed by using smoothing filter?
a) Smooth transitions of gray levels
b) Smooth transitions of brightness levels
c) Sharp transitions of gray levels
d) Sharp transitions of brightness levels
Answer
Answer: c [Reason:] Smoothing filter replaces the value of every pixel in an image by the average value of the gray levels. So, this helps in removing the sharp transitions in the gray levels between the pixels. This is done because, random noise typically consists of sharp transitions in gray levels.
5. Which of the following is the disadvantage of using smoothing filter?
a) Blur edges
b) Blur inner pixels
c) Remove sharp transitions
d) Sharp edges
Answer
Answer: a [Reason:] Edges, which almost always are desirable features of an image, also are characterized by sharp transitions in gray level. So, averaging filters have an undesirable side effect that they blur these edges.
6. Smoothing spatial filters doesn’t smooth the false contours.
a) True
b) False
Answer
Answer: b [Reason:] One of the application of smoothing spatial filters is that, they help in smoothing the false contours that result from using an insufficient number of gray levels.
7. The mask shown in the figure below belongs to which type of filter?
a) Sharpening spatial filter
b) Median filter
c) Sharpening frequency filter
d) Smoothing spatial filter
Answer
Answer: d [Reason:] This is a smoothing spatial filter. This mask yields a so called weighted average, which means that different pixels are multiplied with different coefficient values. This helps in giving much importance to the some pixels at the expense of others.
8. The mask shown in the figure below belongs to which type of filter?
a) Sharpening spatial filter
b) Median filter
c) Smoothing spatial filter
d) Sharpening frequency filter
Answer
Answer: c [Reason:] The mask shown in the figure represents a 3×3 smoothing filter. Use of this filter yields the standard average of the pixels under the mask.
9. Box filter is a type of smoothing filter.
a) True
b) False
Answer
Answer: a [Reason:] A spatial averaging filter or spatial smoothening filter in which all the coefficients are equal is also called as box filter.
10. If the size of the averaging filter used to smooth the original image to first image is 9, then what would be the size of the averaging filter used in smoothing the same original picture to second in second image?
a) 3
b) 5
c) 9
d) 15
Answer
Answer: d [Reason:] We know that, as the size of the filter used in smoothening the original image that is averaging filter increases then the blurring of the image. Since the second image is more blurred than the first image, the window size should be more than 9.
11. Which of the following comes under the application of image blurring?
a) Object detection
b) Gross representation
c) Object motion
d) Image segmentation
Answer
Answer: b [Reason:] An important application of spatial averaging is to blur an image for the purpose of getting a gross representation of interested objects, such that the intensity of the small objects blends with the background and large objects become easy to detect.c
12. Which of the following filters response is based on ranking of pixels?
a) Nonlinear smoothing filters
b) Linear smoothing filters
c) Sharpening filters
d) Geometric mean filter
Answer
Answer: a [Reason:] Order static filters are nonlinear smoothing spatial filters whose response is based on the ordering or ranking the pixels contained in the image area encompassed by the filter, and then replacing the value of the central pixel with the value determined by the ranking result.
13. Median filter belongs to which category of filters?
a) Linear spatial filter
b) Frequency domain filter
c) Order static filter
d) Sharpening filter
Answer
Answer: c [Reason:] The median filter belongs to order static filters, which, as the name implies, replaces the value of the pixel by the median of the gray levels that are present in the neighbourhood of the pixels.
14. Median filters are effective in the presence of impulse noise.
a) True
b) False
Answer
Answer: a [Reason:] Median filters are used to remove impulse noises, also called as salt-and-pepper noise because of its appearance as white and black dots in the image.
15. What is the maximum area of the cluster that can be eliminated by using an n×n median filter?
a) n2
b) n2/2
c) 2*n2
d) n
Answer
Answer: b [Reason:] Isolated clusters of pixels that are light or dark with respect to their neighbours, and whose area is less than n2/2, i.e., half the area of the filter, can be eliminated by using an n×n median filter.
Digital Electronic MCQ Set 5
1. In neighborhood operations working is being done with the value of image pixel in the neighborhood and the corresponding value of a subimage that has same dimension as neighborhood. The subimage is referred as ___
a) Filter
b) Mask
c) Template
d) All of the mentioned
Answer
Answer: d [Reason:] Working in neighborhood operations is done with the value of a subimage having same dimension as neighborhood corresponding to the value in the image pixel. The subimage is called as filter, mask, template, kernel or window.
2. The response for linear spatial filtering is given by the relationship ____
a) Sum of filter coefficient’s product and corresponding image pixel under filter mask
b) Difference of filter coefficient’s product and corresponding image pixel under filter mask
c) Product of filter coefficient’s product and corresponding image pixel under filter mask
d) None of the mentioned
Answer
Answer: a [Reason:] In spatial filtering the mask is moved from point to point and at each point the response is calculated using a predefined relationship. The relationship in linear spatial filtering is given by: the Sum of filter coefficient’s product and corresponding image pixel in area under filter mask.
3. In linear spatial filtering, what is the pixel of the image under mask corresponding to the mask coefficient w (1, -1), assuming a 3*3 mask?
a) f (x, -y)
b) f (x + 1, y)
c) f (x, y – 1)
d) f (x + 1, y – 1)
Answer
Answer: d [Reason:] The pixel corresponding to mask coefficient (a 3*3 mask) w (0, 0) is f (x, y), and so for w (1, -1) is f (x + 1, y – 1).
4. Which of the following is/are a nonlinear operation?
a) Computation of variance
b) Computation of median
c) All of the mentioned
d) None of the mentioned
Answer
Answer: c [Reason:] Computation of variance as well as median comes under nonlinear operation.
5. Which of the following is/are used as basic function in nonlinear filter for noise reduction?
a) Computation of variance
b) Computation of median
c) All of the mentioned
d) None of the mentioned
Answer
Answer: b [Reason:] Computation of median gray-level value in the neighborhood is the basic function of nonlinear filter for noise reduction.
6. In neighborhood operation for spatial filtering if a square mask of size n*n is used it is restricted that the center of mask must be at a distance ≥ (n – 1)/2 pixels from border of image, what happens to the resultant image?
a) The resultant image will be of same size as original image
b) The resultant image will be a little larger size than original image
c) The resultant image will be a little smaller size than original image
d) None of the mentioned
Answer
Answer: c [Reason:] If the center of mask must be at a distance ≥ (n – 1)/2 pixels from border of image, the border pixels won’t get processed under mask and so the resultant image would be of smaller size.
7. Which of the following method is/are used for padding the image?
a) Adding rows and column of 0 or other constant gray level
b) Simply replicating the rows or columns
c) All of the mentioned
d) None of the mentioned
Answer
Answer: c [Reason:] In neighborhood operation for spatial filtering using square mask, padding of original image is done to obtain filtered image of same size as of original image done, by adding rows and column of 0 or other constant gray level or by replicating the rows or columns of the original image.
8. In neighborhood operation for spatial filtering using square mask of n*n, which of the following approach is/are used to obtain a perfectly filtered result irrespective of the size?
a) By padding the image
b) By filtering all the pixels only with the mask section that is fully contained in the image
c) By ensuring that center of mask must be at a distance ≥ (n – 1)/2 pixels from border of image
d) None of the mentioned
Answer
Answer: c [Reason:] By ensuring that center of mask must be at a distance ≥ (n – 1)/2 pixels from border of image, the resultant image would be of smaller size but all the pixels would be the result of the filter processing and so is a fully filtered result.
In the other approach like padding affect the values near the edges that gets more prevalent with mask size increase, while the another approach results in the band of pixels near border that gets processed with partial filter mask. So, not a fully filtered case.
