Image Denoising Based on Quantum Calculus of Local Fractional Entropy

Images are frequently disrupted by noise of all kinds, making image restoration very challenging. There have been many different denoising models proposed over the last few decades. Some preserve image’s smooth region, while others texture margin. One these methods is using quantum calculus. Quantum calculus a branch mathematics that deals with manipulation functions and operators in mechanical setting. It has used processing to improve speed accuracy image-processing algorithms. In computing, entropy can be defined as measure disorder or randomness state. The concept local fractional study wide range systems. this study, an model based on (QC-LFE) remove Gaussian noise. estimate pixel probability, convolution window mask for denoising. A n x elements was suggested algorithm. algorithm uses process each corrupted one at time. algorithm’s effectiveness assessed peak signal-to-noise ratio visual perception (PSNR). experimental findings show that, compared other similar operators, method better details when