Reversible Color Compression Transform for Big Data System Using Human Visual System

Abstract

In today's life, images play a significant role in many Big Data application fields for various purposes. Image processing has to face the huge challenges because of images created in a digital format which leads to huge data volumes. Using Joint Photographic Experts Group 2000 (JPEG2000) compression techniques to meet the diverse type of real-time applications. Lossless compression JPEG2000 and others are used to minimize the expenditure of possessions such as hard disk space and transmission bandwidth. This experimental work shows an improved lossless color image compression that uses a wavelet based Human Visual System.This Reversible Color Compression Transform method (RCCT) produces an efficient algorithm to compress the image without loss of information. JPEG2000 as a lossless mode is utilized for bit-preserving and to refer globally for encoding and decoding processes. The Reversible Color Transform (RCT) is used in JPEG 2000 using wavelets which provide a mathematical way to encode the information in such a way that it is layered according to the level of detail by using HVS attributes in the stage of quantization. In this research, the goal of lossless image compression is to decrease the number of bits required to demand computing resources such as store and transmit images without any loss of information.