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8/7/2019 JPEG encoding

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JPEGCOMPRESSI

ONBy :Sunny Duvani (07MC17)

Satya Bhatt (07MC05)

Harsh Brahmbhatt (07MC06)


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Typical usage

The JPEG compression algorithm is at its best on

photographs and paintings of realistic scenes with smooth

variations of tone and color.

For web usage, where the amount of data used for an

image is important.

JPEG is also not well suited to files that will undergo

multiple edits, as some image quality will usually be lost

each time the image is decompressed and recompressed


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Steps

1. ColorTransformation

2. Down sampling

3. Block Splitting

4. DCT (discrete cosine transform)

5. Quantization & Entropy Encoding

6. Removing Artifacts


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Baseline Sequential JPEG Encodingand Decoding

Processes


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Color space transformation

First, the image should be converted from RGB into a

different color space called YCBCR (or, informally, YCbCr). It

has three components Y', CB and CR: the Y' component

represents the brightness of a pixel, and the CB and

CR components represent the chrominance .

The compression is more efficient because the brightness

information, which is more important to the eventual perceptual

quality of the image, is confined to a single channel. This more

closely corresponds to the perception of color in the human

visual system. The color transformation also improves

compression by statistical decorrelation.


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Downsampling

The transformation into the YCBCR color model to reduce the spatial resolution ofthe Cb and Cr components .The ratios at which the downsampling is ordinarily

done for JPEG images are :

4:4:4 (no downsampling).

4:2:2 (reduction by a factor of 2 in the horizontal direction).

4:2:0 (reduction by a factor of 2 in both the horizontal and vertical directions).

Block splitting

After subsampling, each channel must be split into 88 blocks.

If the data for achannel does not represent an integer num

ber of

block

s then theencoder must fill the remaining area of the incomplete blocks with some form of

dummy data.

Filling the edges with a fixed color (for example, black) can create ringing

artifacts along the visible part of the border.


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DCT (Discrete Cosine Transform)

Each 88 block of each component (Y, Cb, Cr) is converted to a frequency-

domain representation, using a normalized, 2D type-II DCT.

Example : DCT of an 8 x 8 Gray Scale Image

8 x 8 Gray Scale Image


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For an 8-bit image, each entry in the original block falls in the

range [0,255]. The mid-point of the range (in this case, the value 128)

is subtracted from each entry to produce a data range that is centeredaround zero.

so that the modified range is [ 128,127]. This step reduces the

dynamic range requirements in the DCT processing


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TheDiscrete Cosine Functioncan begiven by the Equation

given below :


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Quantization

The human eye is good at seeing small differences in brightness over

a relatively large area, but not so good at distinguishing the exact

strength of a high frequency brightness variation.

This allows one to greatly reduce the amount of information in the

high frequency components.

This is done by simply dividing each component in the frequency

domain by a constant for that component, and then rounding to the

nearest integer.

This rounding operation is the only lossy operation in the whole

process if the DCT computation is performed with sufficiently high

precision.


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Entropy Encoding

Entropy coding is a special form of lossless data compression. It

involves arranging the image components in a "zigzag" order

employing run-length encoding (RLE) algorithm that groups similar

frequencies together, inserting length coding zeros, and thenusing Huffman coding on what is left.

The previous quantized DC coefficient is used to predict the current

quantized DC coefficient. The difference between the two is encoded

rather than the actual value.

The encoding of the 63 quantized AC coefficients does not use such

prediction differencing.


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Compression Ratio & Artifacts

The resulting compression ratio can be varied according to need by

being more or less aggressive in the divisors used in the

quantization phase.

The appropriate level of compression depends on the use to which

the image will be put.

Those who use the World Wide Web may be familiar with the

irregularities known as compression artifacts that appear in JPEG

images, which may take the form of noise around contrasting edges(especially curves and corners), or blocky images, commonly known

as jaggies'.

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