Compression of Stereo Images

1. Compression of Stereo Images John Hamann Vickey Yeh

2. Outline • Basic Algorithm • Color Compression • Motion Compensation • Conclusion

3. Basic Algorithm • Discrete Cosine Transform • Uniform Quantization • No Quantization Tables • Directly Store the DC Coefficients • Huffman Code the AC Coefficients • No Run-Length Encoding • Zip the Final Binary Stream

4. Results

5. Color Compression • Algorithm A • Mode 0: Encode Cr, Cb • Mode 1: Encode Cr, Cb + Cr • Mode 2: Encode Cr, Cb – Cr • Algorithm A Variant • Mode 0: Encode Cb, Cr • Mode 1: Encode Cb, Cr + Cb • Mode 2: Encode Cb, Cr – Cb • Performs Markedly Worse

6. Algorithm A

7. Algorithm A

8. About 1% Improvement

9. Algorithm B • Estimate Cb, Cr based on Y • Cb= acbY + bcb • Cr = acrY + bcr • For each block • Intra-mode • Code acb , acr , bcb , bcb • For small blocks, • Too expensive • For large blocks, • Too much MSE

10. Motion Compensation • Search for Nearest Match • Make Decision Based on Lowest MSE • Give Bonus to Certain Intervals to Cause Clustering of Motion Vectors • Encode the Residuals Using DCT as Before

11. Results

12. Conclusion • Huffman Coding then Zip outperforms • Run-Length Encoding then Huffman Coding • Color Compression Using Algorithm A • 3 Modes of Operation {Cb, Cb+Cr, Cb-Cr} • Provides slight gains • Limited by nature of Cb and Cr • Motion Compensation • Did not prove beneficial

13. Questions