EFFICIENT PLENOPTIC IMAGE COMPRESSION USING RESHAPING AND REGULARIZATION: A NOVEL FRAMEWORK FOR IMPROVED BIT RATE REDUCTION

An effective plenoptic picture compression technique for transmission and storage is needed due to the enormous amount of data. In order to increase compression effectiveness using plenoptic pictures' linear transformation and interpolation, a unique plenoptic image compression framework is thus suggested. Block-based hybrid encoding architecture is used to first shape and regularize a plenoptic image before compressing a raw image. The suggested method performs better than HEVC and JPEG2000 by an average and superior bit rate reduction, when compared to existing picture compression techniques. In recent years, image encryption has gained popularity as a study area. The development of safe image compression methods has received some fresh and effective advice from the chaosbased compression algorithms. One can name compression, for instance. One such advancement in security is data nit reduction, which embeds sensitive data under a cover with a slow data transmission rate. The rapid spread of information and the development of digital technologies have made it easier to access digital information and enabled faster, more efficient storage, transfer, and processing of digital data. This has had the unintended consequence of making it simple and undetectable to produce and distribute digital media illegally.