Image blur and noise are difficult to avoid in many situations
and can often ruin a photograph. We present a novel
image deconvolution algorithm that deblurs and denoises
an ima...
C. Lawrence Zitnick, David J. Kriegman, Neel Joshi...
We propose an effective color image denoising method that exploits ltering in highly sparse local 3D transform domain in each channel of a luminance-chrominance color space. For e...
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik...
Shrinkage is a well known and appealing denoising technique. The use of shrinkage is known to be optimal for Gaussian white noise, provided that the sparsity on the signal's ...
Overcomplete representations are attracting interest in image processing theory, particularly due to their potential to generate sparse representations of data based on their morp...
—We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gau...