An Enhanced Resolution Three-Dimensional Transformation Method Based on Discrete Wavelet Transform

2012 ◽  
Vol 159 ◽  
pp. 41-45
Author(s):  
Ning Tang ◽  
Jin Cai ◽  
Yuan Li
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Video Compression ◽  
Image Coding ◽  
Three Dimensional ◽  
Transformation Method ◽  
Discrete Wavelet ◽  
Compression Algorithms ◽  
Enhanced Resolution ◽  
Embedded Image Coding

With the development of interactive multimedia technologies, image and video compression algorithms necessitated a number of better performance and functionality. Wavelet transform based embedded image coding method is the basis of JPEG2000. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. JPEG2000 algorithm has been developed based on the discrete wavelet transform (DWT) techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance.

Enhanced Three-Dimensional Color Conversion Based on Discrete Wavelet Transform

2012 ◽  
Vol 155-156 ◽  
pp. 440-444
Author(s):  
He Yan ◽  
Xiu Feng Wang
Keyword(s):  
Information Technology ◽  
Wavelet Transform ◽  
Image Reconstruction ◽  
Image Quality ◽  
Image Compression ◽  
High Performance ◽  
Three Dimensional ◽  
Discrete Wavelet ◽  
Compression Algorithms ◽  
Color Conversion

JPEG2000 algorithm has been developed based on the DWT techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. Wavelets have become a popular technology for information redistribution for high-performance image compression algorithms. Lossy compression algorithms sacrifice perfect image reconstruction in favor of improved compression rates while minimizing image quality lossy.

Mobile GPU Computing Based Filter Bank Convolution for Three-Dimensional Wavelet Transform

Biometrics ◽  
2017 ◽  
pp. 761-777
Author(s):  
Di Zhao
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Gpu Computing ◽  
Three Dimensional ◽  
Discrete Wavelet ◽  
Computational Results ◽  
Real Time Processing ◽  
Time Processing ◽  
Mobile Gpu

Mobile GPU computing, or System on Chip with embedded GPU (SoC GPU), becomes in great demand recently. Since these SoCs are designed for mobile devices with real-time applications such as image processing and video processing, high-efficient implementations of wavelet transform are essential for these chips. In this paper, the author develops two SoC GPU based DWT: signal based parallelization for discrete wavelet transform (sDWT) and coefficient based parallelization for discrete wavelet transform (cDWT), and the author evaluates the performance of three-dimensional wavelet transform on SoC GPU Tegra K1. Computational results show that, SoC GPU based DWT is significantly faster than SoC CPU based DWT. Computational results also show that, sDWT can generally satisfy the requirement of real-time processing (30 frames per second) with the image sizes of 352×288, 480×320, 720×480 and 1280×720, while cDWT can only obtain read-time processing with small image sizes of 352×288 and 480×320.

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>

Multi-Spectral Holographic Three-Dimensional Image Fusion Using Discrete Wavelet Transform

2006 ◽  
Vol 2 (4) ◽  
pp. 411-417 ◽  
Author(s):  
Bahram Javidi ◽  
Cuong Manh Do ◽  
Seung-Hyun Hong ◽  
Takanori Nomura
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Three Dimensional ◽  
Discrete Wavelet ◽  
Dimensional Image

Study of the Discrete Wavelet Transform Based on JPEG2000 Image Compression Algorithm

2013 ◽  
Vol 464 ◽  
pp. 411-415
Author(s):  
Jin Cai ◽  
Shuo Wang
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Discrete Wavelet Transform ◽  
Image Coding ◽  
Dynamic Range ◽  
Compression Algorithm ◽  
Discrete Wavelet ◽  
Coding System ◽  
Jpeg 2000 ◽  
Image Compression Algorithm

JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store the image data continue to evolve. The size and bit depth collected for an image to increase the resolution and extend the dynamic range and color gamut. Discrete Wavelet transform based embedded image coding method is the basis of JPEG2000. Image compression algorithm for the proper use and display of the image is a requirement for digital photography.

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