Question
Given an image with uniform histogram. Explain the effect of applying following compression techniques:
i) Huffman,
ii) Golomb,
iii) LZW,
iv) Prediction coding, and
v) Optimal Quantization
Answer :
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Skip in 10
For an image with a uniform histogram, all intensity values occur with roughly equal frequency. The effect of different compression techniques will vary based on how they exploit redundancy or patterns in data: i) Huffman coding: Huffman coding assigns shorter codes to more frequent symbols and longer codes to less frequent symbols. In a uniform histogram, all pixel values have similar frequency, so Huffman coding cannot assign significantly shorter codes. As a result, compression efficiency is very low, and the compressed size is close to the original size. ii) Golomb coding: Golomb coding is effective for data with geometric or exponentially decaying distributions, often used for prediction residuals. Since the histogram is uniform, Golomb coding cannot exploit skewness
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