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Distance-Reciprocal Distortion measure for Binary Document Images

Distance-Reciprocal Distortion measure for Binary Document Images

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Distance-Reciprocal Distortion measure for Binary Document Images

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  1. Distance-Reciprocal Distortion measure for Binary Document Images Author : Haiping Lu, Alex C. Kot, Yun Q. Shi Source : Signal Processing Letters, IEEE , Volume: 11 , Issue: 2 , Feb. 2004 Pages:228 - 231 Adviser : Chin-Chen Chang Speaker : Ming-Hui Ho E-mail : g9234048@pu.edu.tw Date : 2004/5/5

  2. Outline • Binary Document Images • Peak signal-to-noise ratio(PSNR) • PSNR v.s HVS(human visual system) • Distance-Reciprocal Distortion Measure(DRDM) • Experimental Results • Conclusion

  3. Binary Document Images • Binary document images here refer to binary images that have sharp contrast of black and white and there are clear boundaries between black and white areas in the images. • Document images are essentially binary

  4. Peak signal-to-noise ratio(PSNR) • The peak signal-to-noise ratio (PSNR) is a popular distortion measure used in image and video processing. For an image processing system with f(x,y) as the input image and g(x,y) as the processed output image • the PSNR is defined as: • For binary document images , the PSNR does not match well with subjective assessment.

  5. PSNR v.s HVS(human visual system) (a)Original document image (b) Distorted image These four distorted image have the same PSNR

  6. Distance-Reciprocal Distortion Measure(DRDM) • for a binary document image, the distance between two pixels plays a major role in their mutual interference perceived by human eyes.

  7. DRDM-Weight Matrix-table m=5

  8. DRDM

  9. DRDM-NUBN(non-uniform block number) • NUBN is estimate the valid (nonempty) area in the image and it is defined as the number of nonuniform(not all black or white pixels) 8x8 block in f(x,y) Uniform 8x8 block

  10. Experimental

  11. Experimental Results • The subjective assessment is done by 60 observers. • Each set of test images consists of four test images randomly chosen from the four groups. • There are four rankings with score 1 for the least distortion.

  12. Conclusion • Experimental results have shown its high correlation with the subjective assessment. • This measure is useful in wide range of applications involving visual distortion in digital binary document images, such as watermarking,data hiding and lossy compression. • Based on our experimental data , the DRD values for a lage “m” have a slightly lower correlation with the subjective measure. • This distortion measure is not suitable for halftone(dithered) image.