1 / 10

VQ Encoded Image

This study proposes a method to reduce random noise in images by calculating block distances and replacing noisy blocks with neighbors' indices or a lookup table for improvement. The algorithm calculates the mean for each block and evaluates the distance to adjacent blocks to identify noise. By replacing noisy blocks, the algorithm improves the Peak Signal-to-Noise Ratio (PSNR) of the image. Results show a 5% reduction in noise with a 23.9067 dB PSNR and a 10% reduction with a 20.1393 dB PSNR. The study concludes that while block distance reduces noise, further accuracy can be achieved by considering a clique concept. Implementing this algorithm can enhance image quality and reduce noise levels effectively.

idola-knowles
Télécharger la présentation

VQ Encoded Image

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. VQ Encoded Image Ex.3 Kahlil Muchtar D023010006

  2. VQ Encoded Image Original VQ Image PSNR=30.1887

  3. Proposed Method-Block Distance

  4. Algorithm • Calculate the mean for every block (the size is the same as index size) • Calculate the distance between block and its 4 adjacent (N4 neighbours') • If the distance > threshold, it means, the block is regarded as random noise. • If the block is random noise, the index of that block replaced by one of its neighbours index. • Otherwise, corresponding index will be obtained from look up table.

  5. Illustrations Replaced by neighbours index x,y Calculate the Euclidean distance between block and its 4 neighbours. If distance > TH then, …

  6. 5% VQ PSNR = 23.9067 5% VQ Improved PSNR Improved = 25.5726

  7. 10% VQ PSNR = 20.1393 10% VQ Improved PSNR Improved = 22.4339

  8. Conclusions • Block distance can reduce the random noise (5%) but would be less accurate if noise is 10%. • Further improvement, instead of calculating the distance of entire neighbours, the clique concept may increase the accuracy.

  9. Appendix: Noise • intrnd = 0; • for(int y=0;y<height/BlockSize;y++){ • for(int x=0;x<width/BlockSize;x++){ • rnd = rand()%100; • tempx = rnd%(width/BlockSize); • tempy = rnd%(height/BlockSize); • if(rnd<10) // 10% • ClassY[y][x]=ClassY[tempy*BlockSize+y][tempx*BlockSize+x]; • } • }

  10. Appendix: Euclidean Distance • sumdistance = distance2+distance4+distance5+distance7; • if (sumdistance > 250) • { VQYI[y*BlockSize+j][x*BlockSize+i] = VQ[ClassY[y-1][x]][j][i]; • } • else • { • VQYI[y*BlockSize+j][x*BlockSize+i] = VQ[ClassY[y][x]][j][i]; • }

More Related