Image Compression Types

[@asrifarahman1603]

Entropy is a statistical measure of randomness that can be used to characterize the texture of the input image. Entropy is defined as -sum(p. *log2(p)) , where p contains the normalized histogram counts returned from imhist. The entropy of an image can be calculated by calculating at each pixel position (i,j) the entropy of the pixel-values within a 2-dim region centered at (i,j). In the following example the entropy of a grey-scale image is calculated and plotted. The region size is configured to be (2N x 2N) = (10,10)

[@asrifarahman1603]

Coding Redundancy: is a system of symbols(letters,numbers,bits) used to represent a body of information or set of events. Spatial redundancy: pixels of mos. 2-D intesity arrays are correlated spatially (i.e each pixel is similar to or dependent on neighbouring pixel. Irrelevant information: most 2-D intensity arrays contain information that is ignored by human visual system and/or extraneous to the intended use of image.

[@raktimnath3200]

The entropy or average information of an image is a measure of the degree of randomness in the image. The entropy is useful in the context of image coding : it is a lower limit for the average coding length in bits per pixel which can be realized by an optimum coding scheme without any loss of information .

[@djb_world]

Correct!!

[@bino5506]

Elements that are duplicated within a structure, such as pixels in a still image and bit patterns in a file are called spatial redundancy. A resulting image is said to have coding redundancy if its gray levels are coded using more code symbols than actually needed to represent each gray level. Irrelevant information ,most 2-D intensity arrays contain information that is ignored by human visual system and/or extraneous to the intended use of image. The average information per source output is called entropy

[@djb_world]

Very Good , Binoy..Thats Correct!!

[@GearAxom]

Coding Redundancy: is a system of symbols(letters,numbers,bits) used to represent a body of information or set of events. Spatial redundancy: pixels of mos. 2-D intesity arrays are correlated spatially (i.e each pixel is similar to or dependent on neighbouring pixel. Irrelevant information: most 2-D intensity arrays contain information that is ignored by human visual system and/or extraneous to the intended use of image. ~Kritartha

[@djb_world]

Good Kritartha

[@debashreesarmah3571]

Entropy gives a measure of uncertainty about its actual structure. The Entropy of an image could be used for measuring its visual aspects or for gathering information to be used as parameters in some systems.

[@djb_world]

Correct!!

[@Miss_kaberi_vlogs]

The entropy or average information of an image is a measure of the degree of randomness in the image.The entropy is useful in the context of image coding : it is a lower limit for the average coding length in bits per pixel which can be realized by an optimum coding scheme without any loss of information .

[@princepolinsaikia1279]

Entropy is a statistical measure of randomness that can be used to characterize the texture of the input image. Entropy is defined as -sum(p. *log2(p)) , where p contains the normalized histogram counts returned from imhist. The entropy of an image can be calculated by calculating at each pixel position (i,j) the entropy of the pixel-values within a 2-dim region centered at (i,j). In the following example the entropy of a grey-scale image is calculated and plotted. The region size is configured to be (2N x 2N) = (10,10)

[@AryanRaj_1198]

Coding Redundancy: is a system of symbols(letters,numbers,bits) used to represent a body of information or set of events. Spatial redundancy: pixels of mos. 2-D intesity arrays are correlated spatially (i.e each pixel is similar to or dependent on neighbouring pixel. Irrelevant information: most 2-D intensity arrays contain information that is ignored by human visual system and/or extraneous to the intended use of image.