Rule of Three for Superresolution of Still Images with Applications to Compression and Denoising
This work addresses image compression and denoising for applications like JPEG, but it is incremental as it builds on existing wavelet domain techniques.
The paper tackles the problem of superresolution for still images in the wavelet domain by using a Rule of Three method to reconstruct missing detail subband pixels, which improves compression rates and denoising compared to typical methods.
We describe a new method for superresolution of still images (in the wavelet domain) based on the reconstruction of missing details subbands pixels at a given ith level via Rule of Three (Ro3) between pixels of approximation subband of such level, and pixels of approximation and detail subbands of (i+1)th level. The histogramic profiles demonstrate that Ro3 is the appropriate mechanism to recover missing detail subband pixels in these cases. Besides, with the elimination of the details subbands pixels (in an eventual compression scheme), we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain. Our method does not compress, but facilitates the action of the real compressor, in our case, Joint Photographic Experts Group (JPEG) and JPEg2000, that is, Ro3 acts as a catalyst compression