Prediction-based coding

1. Prediction-based coding

2. Input Image Compressed Coded Image Nonuniform quantizer Statistical coder PREDICTOR DPCM coding Dr.E. Regentova

3. “Past” samples - 0.2 - 0.3 - 0.2 Current pixel - 0.3 “Future” samples 2-D prediction for row-column scanning method Dr.E. Regentova

4. Compressed Image Decompressed Image Statistical decoder Predictor DPCM Decompression Dr.E. Regentova

5. Coding differential image Compression ratio is about 2.5(1-3) Dr.E. Regentova

6. Input image; std=52.85 Input image histogram Histogram of horizontal differences 6000 500 5000 400 4000 300 3000 200 2000 100 1000 0 0 50 100 150 200 250 50 100 150 200 250 Horizontal differences;std=22.4565 Dr.E. Regentova

7. Horizontal differences; std=22.4565 Histogram of horizontal differences Vertical differences; std=17.0269 Histogram of vertical differences 7000 6000 5000 4000 3000 2000 1000 0 250 50 100 150 200 6000 5000 4000 3000 2000 1000 0 200 250 50 100 150 Dr.E. Regentova

8. Coding Example DPCM_1D; rate=3 b/pixel , Std of the restoration error 6.67 Lena Dr.E. Regentova

9. Find the horisontal prediction error J=double(imread('cameraman.tif')); for x= 2:1:256 for y=1:1:256 o=x-1; ImDiff(x,y)= uint16((abs(J(x,y)-J(o,y)))); end end image(ImDiff(:,:); K= double(ImDiff); hist(K); Dr.E. Regentova