Digital Image Processing | General Questions & Answers 2021
Q. Define Image?
Q. What do you meant by gray level?
Ans: Gray level refers to a scalar measure of intensity that ranges from black to grays and finally to white.
Q. Define dilation?
Ans: Dilation is a basic morphological operation which is used for expanding an element A by using structuring element B.
Q. Define erosion?
Ans: Erosion is a basic morphological operation which is used for shrinking of element A by using element B.
Q. Define opening?
Ans: Opening is First erode A by B, and then dilate the result by B. In other words, opening is the unification of all B objects Entirely Contained in A. Opening smoothes contours , eliminates protrusions.
Q. Define closing?
Q. Define Image Segmentation?
Ans: The histogram equalization is an approach to enhance a given image. The approach is to design a transformation T(.) such that the gray values in the output is uniformly distributed in [0, 1].
Q. Define Image enhancement?
Ans: Image enhancement is the process of manipulating an image so that the result is more suitable than the original for a specific application.
Q. What is Lossless compression?
Ans: Lossless compression is a type of compression that removes only redundant information.
Q. What is Lossy compression?
Ans: Lossy compression is a type of compression that deliberately sacrifices some of the original data in return for much higher compression ratios than those achievable with lossless techniques.
Q. Define compression ratio?
Ans: The ratio of the original, uncompressed image file and the compressed file is referred to as the compression ratio.
Q. Define Histogram of an image?
Ans: Histogram of an image represent the relative frequency of occurance of the various grey levels in an image.
Q. Define region growing?
Ans: Region growing is a procedure in which pixels are grouped into larger regions based on some predefined condition.
Q. Define sampling & quantization?
Ans: Digitizing the coordinate values is called sampling. Digitizing the amplitude values is called quantization.
Ans: An Image may be defined as a two dimensional function f (x,y) where x & y are spatial (plane) coordinates, and the amplitude of f at any pair of coordinates (x,y) is called intensity or gray level of the image at that point.
Q. What do you meant by gray level?
Ans: Gray level refers to a scalar measure of intensity that ranges from black to grays and finally to white.
Q. What is meant by pixel?
Ans: A digital image is composed of a finite number of elements each of which has a particular location or value. These elements are referred to as pixels or image elements or picture elements or pixels elements.
Ans: Dilation is a basic morphological operation which is used for expanding an element A by using structuring element B.
Q. Define erosion?
Ans: Erosion is a basic morphological operation which is used for shrinking of element A by using element B.
Q. Define opening?
Ans: Opening is First erode A by B, and then dilate the result by B. In other words, opening is the unification of all B objects Entirely Contained in A. Opening smoothes contours , eliminates protrusions.
Q. Define closing?
Ans: Closing is First dilate A by B, and then erode the result by B. In other words, closing is the group of points, which the intersection of object B around them with object A is not empty.
Closing smoothes sections of contours, fuses narrow breaks and long thin gulfs, eliminates small holes and fills gaps in contours.
Q. Define Image Segmentation?
Ans: Image segmentation is attempts to partition the pixels of an image into groups that strongly correlate with the objects in an image.
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Q. What is the histogram equalization?Ans: The histogram equalization is an approach to enhance a given image. The approach is to design a transformation T(.) such that the gray values in the output is uniformly distributed in [0, 1].
Q. Define Image enhancement?
Ans: Image enhancement is the process of manipulating an image so that the result is more suitable than the original for a specific application.
Q. What is Lossless compression?
Ans: Lossless compression is a type of compression that removes only redundant information.
Q. What is Lossy compression?
Ans: Lossy compression is a type of compression that deliberately sacrifices some of the original data in return for much higher compression ratios than those achievable with lossless techniques.
Q. Define compression ratio?
Ans: The ratio of the original, uncompressed image file and the compressed file is referred to as the compression ratio.
Q. Define Histogram of an image?
Ans: Histogram of an image represent the relative frequency of occurance of the various grey levels in an image.
Q. Define region growing?
Ans: Region growing is a procedure in which pixels are grouped into larger regions based on some predefined condition.
Q. Define sampling & quantization?
Ans: Digitizing the coordinate values is called sampling. Digitizing the amplitude values is called quantization.
Ans: Hue is a color attribute that describes a pure color where saturation gives a measure of the degree to which a pure color is diluted by white light.
Q. Properties of DCT(Discrete Cosine Transform)?
Ans: (1) It is real & orthogonal.
(2) It is fast transform.
(3) It can be calculated in Nlog2N operations via N-point transform.
(4) It is good for energy compaction for highly correlated data.
(5) It can be used for designing transform code & wiener filter.
(6) It is used for JPEG compression.
Q. Properties of Hadamard transform?
Q. Properties Discrete Sine Transform?
Ans: (1) It is symmetrical, real & orthogonal.
(2) It is faster than DCT.
(3) It is calculated by Nlog2N via 2(N+1) point FFT.
(4) It has very good energy compression property for images.
(5) It is used for estimating performances in digital image processing problems.
(2) It is fast transform.
(3) It can be calculated in Nlog2N operations via N-point transform.
(4) It is good for energy compaction for highly correlated data.
(5) It can be used for designing transform code & wiener filter.
(6) It is used for JPEG compression.
Q. Properties of Hadamard transform?
Ans: (1) Hadamard Transform H is real, symmetric &orthogonal.
(2) It is fast transform (faster than DCT). The 1D transformation can be implemented in Nlog2N additions and subtraction. Since HT contain only +/- values, no multiplications are required in the calculations.
(3) It has very good energy compression for highly correlated images.
(4) It is useful in hardware implementation for DFT algorithm, used in image, data compression, filtering and designing of codes.
Q. Properties Discrete Sine Transform?
Ans: (1) It is symmetrical, real & orthogonal.
(2) It is faster than DCT.
(3) It is calculated by Nlog2N via 2(N+1) point FFT.
(4) It has very good energy compression property for images.
(5) It is used for estimating performances in digital image processing problems.
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