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Capable of compressing continuous-tone image data with a pixel depth of 6 to 24 bits with reasonable speed and efficiency.
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Lossy compression, but tries to limit loss to what human eye canšt see. Good quality images can be reproduced from files compressed at 25:1.
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Toolkit of compression methods: parameters can be chosen to vary image quality versus storage size.
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Works best on photographs or natural images, not good on single color areas.
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Compression scheme:
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Transform the image into an optimal color space. Convert RGB to YCrCb.
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Downsample chrominace components. Since the eye is most sensitive to the luminence, keep the Y value for each pixel, but only keep 1/4 of the CrCb components, one average value for every 2x2 pixel block.
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Apply a Discrete Cosine Transform to 8 by 8 blocks, separating high and low-frequency information. This is the most time-consuming part of the transform.
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Quantize each block with functions weighted for the human eye. This is the step affected most by the Q factor to decide how much high-frequency information to discard.
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Encode resulting coefficients using a Huffman algorithm.
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