快速Linde-Buzo-Gray (FLBG) 算法用于通过使用双线插值进行重新缩放的图像压缩

相关实验视频

Updated: Jun 25, 2025

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Muhammmad Bilal¹, Zahid Ullah², Omer Mujahid³

¹Department of Information Engineering Technology, University of Technology, Nowshera 24170, Pakistan.

Journal of imaging

|May 24, 2024

概括

这项研究介绍了一种增强的林德-布佐-格雷 (LBG) 算法,用于矢量量化 (VQ) 图像压缩. 改进的方法显著降低了计算复杂性和内存大小,同时保持了图像质量.

科学领域:

数字图像处理是数字图像处理.
数据压缩算法数据压缩算法
信息理论是信息理论.

背景情况:

矢量量化 (VQ) 提供了高压缩比和简单的实现.
林德-布佐-格雷 (LBG) 是一个标准的VQ代码书设计技术.
现有的基于LBG的优化算法 (PSO,CS,FA) 由于彻底的搜索而遭受高计算时间的损失.

研究的目的:

改进用于矢量量化 (VQ) 的林德-布佐-格雷 (LBG) 算法.
为了尽量减少图像压缩中的计算复杂性和内存要求.
在压缩过程中保持高图像质量 (PSNR,SSIM).

主要方法:

开发了一种新的算法,通过减少代码书和训练矢量之间的比较来增强LBG.
利用匹配函数和通过近邻方法与近邻方法的二线性插值进行重新缩放.
在编码器实现了图像缩小,在解码器实现了缩放.

主要成果:

与标准的LBG.BG相比,计算复杂度减少了50.2%.
与其他基于LBG的优化算法相比,计算复杂度降低了97%以上.
在图像质量没有显著损失的情况下,获得了20%的内存大小减少.

结论:

提议的增强LBG算法为VQ图像压缩提供了计算效率和内存使用的显著改进.
该方法有效地平衡了压缩性能和图像保真度.
这种方法为高效的图像压缩技术提供了实际的进步.

关键词:

林德布佐格雷在线播放蝙蝠算法是一种算法.代码书是一个代码书.计算时间计算时间.火虫算法是一种算法.图像压缩图像压缩峰值信号与噪声比率的比率.矢量量化定量化矢量量化量化

更多相关视频

Analyzing Dendritic Morphology in Columns and Layers

Analyzing Dendritic Morphology in Columns and Layers

Published on: March 23, 2017

Quantifying Intermembrane Distances with Serial Image Dilations

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

相关概念视频

Reconstruction of Signal using Interpolation

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...

Upsampling

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...