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MATLAB Program for 4:2:0 Image Compression and Signal Processing Concepts

This assignment involves creating a MATLAB program to implement the 4:2:0 image compression technique, where B is the reconstructed image derived from input color image A using interpolation. The coded file should be submitted via email. Additionally, questions explore the phenomenon of harmony in music signals, challenges in speech recognition, appropriateness of DCT over DFT and KLT for image compression, and concepts related to cepstrum, NRMSE, and Huffman coding in the trinary system. This work will be assessed based on specified scoring.

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MATLAB Program for 4:2:0 Image Compression and Signal Processing Concepts

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  1. Homework 3 (Due: 5/16th) • Write the Matlab program for the 4:2:0 image compression technique. • B = C420(A), A is the input color image and B is the reconstructed image. • Just use the interpolation method for reconstruction. The Matlab file should be mailed to me. (25 scores) (2) (a) Why the music signals always have the chord phenomena (b) Why the speech signal is harder to recognize than the music signal? (15 scores) (3) Why using the DCT for image compression is more suitable than using the DFT and the KLT ? (10 scores) (4) Suppose that the cepstrum of a signal x[n] is Determine x[n]using the Z transform and exp( ). (10 scores)

  2. (5) (a) Why the normalized root mean square error (NRMSE) may not reflect the similarity between two images? (8 scores) (b) Can the NRMSE measure the similarity between two audio signals? Why? (7 scores) (6) Suppose that P(x = n) = 0.001 ×2n for n = 0, 1, …, 8, P(x = 9) = 0.489. (a) Determine the coding tree for x when using the Huffman code in the trinary (三進位) system. (10 scores) (b) Suppose that length(x) = 10,000. Estimate the range of the total codinglengths in the k-ary (k進位) system when using (i) the Huffman code and (ii) the arithmetic code. (15 scores)

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