scholarly journals Comparative Compression of Wavelet Haar Transformation with Discrete Wavelet Transform on Colored Image Compression

2020 ◽  
Vol 3 (2) ◽  
pp. 202-209
Author(s):  
Christnatalis Christnatalis ◽  
Bachtiar Bachtiar ◽  
Rony Rony
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Discrete Wavelet Transform ◽  
Wavelet Transforms ◽  
Wavelet Transformation ◽  
Haar Wavelet ◽  
Transformation Method ◽  
Discrete Wavelet ◽  
Digital Image Compression ◽  
The Right

In this research, the algorithm used to compress images is using the haar wavelet transformation method and the discrete wavelet transform algorithm. The image compression based on Wavelet Wavelet transform uses a calculation system with decomposition with row direction and decomposition with column direction. While discrete wavelet transform-based image compression, the size of the compressed image produced will be more optimal because some information that is not so useful, not so felt, and not so seen by humans will be eliminated so that humans still assume that the data can still be used even though it is compressed. The data used are data taken directly, so the test results are obtained that digital image compression based on Wavelet Wavelet Transformation gets a compression ratio of 41%, while the discrete wavelet transform reaches 29.5%. Based on research problems regarding the efficiency of storage media, it can be concluded that the right algorithm to choose is the Haar Wavelet transformation algorithm. To improve compression results it is recommended to use wavelet transforms other than haar, such as daubechies, symlets, and so on.

VLSI Architectures for Lifting Based Discrete Wavelet Transform – A Survey

2016 ◽  
Vol 3 (2) ◽  
pp. 323
Author(s):  
M. Kalaiarasi ◽  
T. Vigneswaran
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Discrete Wavelet Transform ◽  
Video Compression ◽  
Perfect Reconstruction ◽  
Discrete Wavelet ◽  
Vlsi Architectures ◽  
3 Dimensional ◽  
Recursive Structures ◽  
Memory Power

<p>Image compression is a key technology in the development of various multimedia and communication applications. Perfect reconstruction of the image without any loss in picture quality and data is very important. This can be achieved with the Discrete Wavelet Transform (DWT), which is an efficient tool for image compression and video compression. The lifting based DWT architecture has the advantage of lower computational complexities and also requires less memory compared to the conventional convolution method. The existing DWT architectures are represented in terms of folded, flipping and recursive structures. The various architectures are discussed in terms of memory, power consumption and operating frequency involved with the given size of image and required levels of decomposition. This paper presents a survey of these architectures for 2-dimensional and 3-dimensional Discrete Wavelet Transform. This study is useful for deriving an efficient method for improving the speed and hardware complexities of existing architectures.</p>

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