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Enhanced Image Compression and Processing Scheme

机译：增强的图像压缩和处理方案

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Image compression refers to the process of encoding image using fewer number of bits. The major aim of lossless image compression is to reduce the redundancy and irreverence of image data for better storage and transmission of data in the better form. The lossy compression scheme leads to high compression ratio while the image experiences lost in quality. However, there are many cases where the loss of image quality or information due to compression needs to be avoided, such as medical, artistic and scientific images. Efficient lossless compression become paramount, although the lossy compressed images are usually satisfactory in divers’ cases. This paper titled Enhanced Lossless Image Compression Scheme is aimed at providing an enhanced lossless image compression scheme based on Bose, Chaudhuri Hocquenghem- Lempel Ziv Welch (BCH-LZW) lossless image compression scheme using Gaussian filter for image enhancement and noise reduction. In this paper, an efficient and effective lossless image compression technique based on LZW- BCH lossless image compression to reduce redundancies in the image was presented and image enhancement using Gaussian filter algorithm was demonstrated. Secondary method of data collection was used to collect the data. Standard research images were used to validate the new scheme. To achieve these, an object approach using Java net beans was used to develop the compression scheme. From the findings, it was revealed that the average compression ratio of the enhanced lossless image compression scheme was 1.6489 and the average bit per pixel was 5.416667. Gaussian filter image enhancement was used for noise reduction and the image was enhanced eight times the original.
机译：图像压缩是指使用较少数量的比特编码图像的过程。无损图像压缩的主要目的是降低图像数据的冗余和不验证，以便以更好的形式更好地存储和传输数据。损失压缩方案导致高压缩比，而图像质量损失。然而，需要避免许多情况，其中需要避免由于压缩引起的图像质量或信息丢失，例如医疗，艺术和科学图像。有效的无损压缩变得至高无径，尽管损失的压缩图像通常在潜水员的情况下令人满意。本文标题为增强的无损图像压缩方案，旨在提供基于Bose的增强的无损图像压缩方案，Chaudhuri Hocquenghem-Lempel Ziv Welch（BCH-LZW）无损图像压缩方案，用于使用高斯滤波器进行图像增强和降噪。本文介绍了基于LZW-BCH无损图像压缩的有效且有效的无损图像压缩技术，以减少图像中的图像中的冗余，并使用高斯滤波器算法进行图像增强。使用辅助方法的数据收集来收集数据。标准研究图像用于验证新方案。为实现这些，使用Java Net Beans的对象方法来开发压缩方案。从调查结果开始，揭示了增强型无损图像压缩方案的平均压缩比为1.6489，每像素的平均钻头为5.416667。高斯滤波器图像增强用于降噪，图像增强了原件的八倍。

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