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

机译:使用人类视觉系统的大数据系统可逆颜色压缩转换

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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.
机译:在当今的生活中,出于各种目的,图像在许多大数据应用领域中发挥着重要作用。由于以数字格式创建的图像会导致巨大的数据量,因此图像处理必须面对巨大的挑战。使用联合图像专家组2000(JPEG2000)压缩技术来满足各种类型的实时应用程序。使用无损压缩JPEG2000和其他压缩技术可以最大程度地减少诸如硬盘空间和传输带宽之类的财产支出。此实验工作展示了一种改进的无损彩色图像压缩,该压缩使用基于小波的人眼视觉系统。此可逆彩色压缩变换方法(RCCT)产生了一种有效的算法来压缩图像而不会丢失信息。 JPEG2000作为一种无损模式,用于保留位并全局引用以进行编码和解码过程。可逆颜色变换(RCT)在使用小波的JPEG 2000中使用,该小波提供了一种数学方式来对信息进行编码,以便在量化阶段通过使用HVS属性根据详细程度对信息进行分层。在这项研究中,无损图像压缩的目标是减少要求计算资源(例如存储和传输图像)所需的位数,而不会丢失任何信息。

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