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Accelerated implementation method of DCT algorithm and DWT algorithm based on CUDA architecture for image compression

A technology of image compression and implementation method, which is applied in the field of image processing, can solve the problem of low compression rate and achieve the effect of increasing the compression rate

Active Publication Date: 2019-03-08
BEIJING INST OF AEROSPACE CONTROL DEVICES +1
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of low compression rate in the existing image processing means, and propose a method for realizing the accelerated implementation method of DCT algorithm and DWT algorithm based on CUDA architecture for image compression

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  • Accelerated implementation method of DCT algorithm and DWT algorithm based on CUDA architecture for image compression
  • Accelerated implementation method of DCT algorithm and DWT algorithm based on CUDA architecture for image compression
  • Accelerated implementation method of DCT algorithm and DWT algorithm based on CUDA architecture for image compression

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specific Embodiment approach 1

[0027] The accelerated implementation method of the DCT algorithm based on the CUDA architecture for image compression of the present embodiment, the method is implemented by the following steps:

[0028] Step 1, analyze the software system and hardware system of the CUDA platform, and build the CUDA platform based on VS2010 under the Windows operating system; wherein, CUDA refers to the unified computing device architecture, which is the abbreviation of Compute Unified Device Architecture; VS2010 refers to Microsoft Visual Studio 2010 version, It is a Windows platform application development environment launched by Microsoft;

[0029] Step 2, at first, realize the running of serial DCT algorithm on CPU, be used for contrasting with the method of the present invention; DCT algorithm is mapped as the kernel function of two-layer CUDA execution model, obtains improved DCT algorithm, realizes improved DCT algorithm Running on the GPU side; DCT algorithm refers to discrete cosine ...

specific Embodiment approach 2

[0031] Different from the specific embodiment one, the method for accelerating the implementation of the DCT algorithm based on the CUDA architecture for image compression of the present embodiment, the specific process of building the CUDA platform based on VS2010 under the Windows operating system described in step one is:

[0032] The 1st, described Windows operating system is selected as WIN732 bit flagship edition operating system, and program development environment builds based on Visual Studio 2010, and described CUDA version is CUDA4.0,

[0033] 2. Prepare the following software packages:

[0034] Microsoft Visual Studio 2010, referred to as VS2010,

[0035] Driver: devdriver_4.0_winvista-win7_32_275.33_notebook.exe, for the graphics card driver

[0036] CUDA Toolkit v4.0: cudatoolkit_4.0.17_win_32.msi,

[0037] CUDA SDK v4.0: gpucomputingsdk_4.0.19_win_32.exe,

[0038] Visual Assist X, a plug-in assistant for VS2010,

[0039] Parallel Nsight v2.0: Parallel_Nsight...

specific Embodiment approach 3

[0055] The difference from specific embodiment 1 or 2 is that, in the accelerated implementation method of the CUDA architecture-based DCT algorithm for image compression in this embodiment, the process of implementing the serial DCT algorithm on the CPU described in step 2 is as follows: The relevant information of the CPU processor is as follows:

[0056]

[0057]

[0058] Such as figure 2 As shown, the serial operation process of the DCT algorithm is: input image; then allocate storage space; then convert byte type to float type; then each pixel value -128; then calculate each coefficient of the first block, repeat the above steps to the last block After the processing is completed; after that, IDCT algorithm processing is performed; after that, each pixel value is +128; after that, the float type is converted to byte type; after that, the image is generated; after that, the PSNR and output time are calculated; after that, the storage space is released; and finally e...

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Abstract

The invention provides an accelerated implementation method of a DCT algorithm and a DWT algorithm based on a CUDA architecture for image compression, and belongs to the field of image compression. The existing image processing means has a problem of low compression rate. The accelerated implementation method of the DCT algorithm and the DWT algorithm based on the CUDA architecture for image compression comprises the following steps: analyzing the software system and a hardware system of s CUDA platform, and building the CUDA platform based on VS2010 under an Windows operating system; respectively mapping the DCT algorithm and the DWT algorithm into kernel functions of a two-layer CUDA execution model to obtain an improved DCT algorithm and an improved DWT algorithm, and respectively running the improved DCT algorithm and the improved DWT algorithm on a GPU end; and running the improved DCT algorithm on the CUDA platform. The accelerated implementation method provided by the inventionis applicable to the implementation of the DCT algorithm and the DWT algorithm on the CUDA platform. A compression ratio several times greater than that of the CPU can be obtained in a parallel execution operation process, so that the compression rate of compressing digital images can be effectively improved.

Description

technical field [0001] The invention relates to an image processing method, in particular to an accelerated realization method of a DCT algorithm and a DWT algorithm based on CUDA framework for image compression. Background technique [0002] Today, society has entered the information age, and digital images have become an important means for people to obtain and exchange information because of their large amount of information and the characteristics of easy processing. The application fields of image processing involve all aspects of human life and work, including aerospace, biomedical engineering, communication engineering technology applications, industrial engineering, military public security, and culture and art. However, digital images have a large amount of data, and information transmission and storage become difficult. Therefore, it is very necessary to study image compression technology to reduce the amount of image data, especially with the rapid development of...

Claims

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Application Information

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IPC IPC(8): H04N19/42H04N19/625H04N19/436
CPCH04N19/42H04N19/436H04N19/625
Inventor 滑艺陈浩牛文龙
Owner BEIJING INST OF AEROSPACE CONTROL DEVICES
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