Compression of images with a mathematical approach based on sine and cosine equations and vector quantization (VQ)

Compressing the image causes less memory to be used store images. images increases transmission speed of compressed in network. Vector quantization (VQ) is one compression methods. The challenge vector method for non-optimization codebooks. Codebook optimization quality and reduces volume Various methods swarm intelligence meta-heuristics are improve algorithm, but using meta-heuristic based on mathematical sciences has history. This paper uses an improved sine–cosine algorithm (SCA) version optimize reduce error. reason SCA balance between search exploration exploitation by sine cosine functions, which makes it likely get caught local optima. proposed calculation error spiral trigonometric functions a new helix. searches optimal solutions with snail searches, increasing chances finding more solutions. aims find codebook VQ algorithm. advantage codebooks implementing MATLAB software, experiments showed that method's PSNR index improves algorithm's ratio 13.73%. Evaluations show higher better than PBM, CS-LBG, FA-LBG, BA-LBG, HBMO-LBG, QPSO-LBG, PSO-LBG. result shows (or ISCA-LBG) time complexity HHO WOA algorithms.