The Image Compression Technology Based on Wavelet Transform

2014 ◽  
Vol 1078 ◽  
pp. 370-374
Author(s):  
Wen Jing Zhao ◽  
Ming Jun Zhao ◽  
Jian Pan
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Data Compression ◽  
Image Data ◽  
Redundant Information ◽  
Two Dimensional ◽  
Key Technology ◽  
The Core ◽  
Core Technology ◽  
Wavelet Image

Image compression is a data compression technology used in the digital image, its purpose is to reduce redundant information of the image data, and provide a more efficient format to store and transmit data. Due to the huge image data and the existing relatively low transport conditions, the image compression has become an inevitable. The key technology of image compression is how to transform image data, how to quantify image data, and how to entropy code the quantized data. Using two-dimensional Mallat image wavelet compression algorithm is a new method of image compression, and it is the core technology of the wavelet image compression.

scholarly journals Comparative Study of Wavelet Image Compression: JPEG2000 Standart

2015 ◽  
Vol 16 (1) ◽  
pp. 83
Author(s):  
Ansam Ennaciri ◽  
Mohammed Erritali ◽  
Mustapha Mabrouki ◽  
Jamaa Bengourram
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Compression Ratio ◽  
Image Data ◽  
Discrete Wavelet ◽  
Original Image ◽  
Essential Quality ◽  
Image Data Compression ◽  
Wavelet Image

The objective of this paper is to study the main characteristics of wavelets that affect the image compression by using the discrete wavelet transform and lead to an image data compression while preserving the essential quality of the original image. This implies a good compromise between the image compression ratio and the PSNR (Peak Signal Noise Ration).

Image Compression Technology Based on the Analysis Theory of Wavelet

2012 ◽  
Vol 160 ◽  
pp. 400-404
Author(s):  
Hui Guo ◽  
Jie He
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
Quantitative Data ◽  
Image Data ◽  
Compression Algorithm ◽  
Compression Method ◽  
Huge Amount ◽  
Analysis Theory ◽  
Wavelet Image ◽  
Image Compression Algorithm

Due to the huge amount of image data transmission conditions and the existing relative low, makes the image compression become inevitable, key technology of image compression for image data transform to transform the quantitative data, as well as to the quantitative data, after the entropy coding.And this article USES the 2 d Mallat of wavelet image compression algorithm is a kind of common image compression method of wavelet image compression algorithm is the core.

An Improved Method for Remote Sensing Image Compression

2014 ◽  
Vol 543-547 ◽  
pp. 2681-2686
Author(s):  
Shuai Xue ◽  
Qing Dai
Keyword(s):  
Remote Sensing ◽  
Wavelet Transform ◽  
Image Compression ◽  
Text Analysis ◽  
Image Data ◽  
Remote Sensing Image ◽  
Integer Wavelet Transform ◽  
Improved Method ◽  
Integer Wavelet ◽  
And Storage

Consider of the characteristics of quantity of remote sensing image data, in order to transport and storage them easily, the text analysis and research some compression technology about remote sensing image, and make compares among them, then propose an optimized method based on integer wavelet transform about image compression. This method encodes the lowest frequency sub-band and high.

An Approach to Diminish Boundary Distortion in Compressing Grid DEM with Discrete Wavelet Transform

2012 ◽  
Vol 220-223 ◽  
pp. 2617-2621
Author(s):  
Zhan Qiang Chang ◽  
Xiao Meng Liu ◽  
Zu Rui Ao
Keyword(s):  
Wavelet Transform ◽  
Spatial Analysis ◽  
Data Compression ◽  
Discrete Wavelet Transform ◽  
Digital Elevation Model ◽  
High Accuracy ◽  
Discrete Wavelet ◽  
The Core ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, the core data for 3-dimensinal visualization and spatial analysis, plays a key role in geosciences and GIS, and wavelet transform is an important tool for data compression. According to the characteristics of DEM data and wavelet transform, we proposed an approach to diminish boundary distortion in compressing grid DEM data with discrete wavelet transform, so that the compression performances are evidently improved. The experimental results indicate that not only higher compression ratios but also reconstructed DEM data with high accuracy are achieved by using the proposed approach.

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