基于非下采样contourlet变换自适应阈值图像去噪方法研究.doc
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基于非下采样contourlet变换自适应阈值图像去噪方法研究,基于非下采样contourlet变换自适应阈值图像去噪方法研究1.67万字自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用摘要： 图像去噪是图像增强、分割、识别等后续图像处理的必要环节，contourlet去噪算法和基于非下采样contourlet变换自适应阈值图像去噪方法日益受到学者的关注。本文阐述了基于...
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基于非下采样Contourlet变换自适应阈值图像去噪方法研究
1.67万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要： 图像去噪是图像增强、分割、识别等后续图像处理的必要环节，Contourlet去噪算法和基于非下采样Contourlet变换自适应阈值图像去噪方法日益受到学者的关注。本文阐述了基于多尺度多方向图像去噪算法的原理、方法和实现过程，对Contourlet和非下采样Contourlet理论做了详细讲解并对Contourlet和非下采样自适应阈值去噪算法进行了分析，在开发软件MATLAB7.0进行了仿真。本文重点分析基于非下采样Contourlet变换自适应阈值图像去噪方法。首先对噪声图像进行非下采样Contourlet变换，得到各个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值。实验表明，与Contourlet多尺度阈值去噪、Contourlet自适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR值, 减少了Gibbs现象。
关键词： Contourlet变换 非下采样Contourlet变换 图像去噪 阈值
Research of Image De-Noising Algorithm Using Adaptive Threshold Based on Non Subsampled Contourlet Transform
Abstract ：Image denoising is an essential process for image enhancement, segmentation and recognition. Recently the denoising method based on Contourlet Transform and nonsubsampled contourlet transform is becoming more and more attention by scholars. This paper describes the image denoising theory based on multi-scale and multi-directions transform, introduces the denoising method based on the wavelet and contourlet transform adaptive threshold algorithm, and stimulate in matlab7.0, the results were satisfactory. A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform (NSCT) is importantly presented. The noised image is firstly decomposed into a set of multiscale and multidirectional frequency subbands by NSCT, the threshold is adapted automatically according to the energy of subband coefficients. Comparing with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform , the simulation results show that the performance of this method is superior in psnr, meanwhile it can maintain the image edge and reduce the Gibbs phenomena.
Keywords ：Contourlet Transform onsubsampled contourlet transform Digital Image Process threshold
目 录
第一章 绪论 1
1.1 图像去噪的基本概念 1
1.2 图像去噪研究的背景、现状及其意义 2
1.3 课题研究的背景、意义及其发展 3
第二章 传统的图像去噪算法 6
2.1 基于小波分析的图像去噪 6
2.2 基于多尺度几何分析的图像去噪 8
第三章 Contourlet去噪变换方法 11
3.1 基于Contourlet的图像去噪的内容 11
3.2 基于Contourlet的图像去噪的仿真与结果 11
第四章 非下采样Contourlet变换去噪方法 18
4.1 非下采样 Contourlet 变换 18
4.1.1 非下采样 Contourlet 变换的内容 18
4.1.2 NSCT自适应阈值去噪原理 20
4.2 基于非下采样Contourlet的图像去噪的仿真与结果分析 22
4.2.1 对图像NSCT 变换去噪仿真 22
4.2.2 对图像进行NSCT变换去噪仿真结果分析 23
第五章 总结 26
5.1 结论 26
5.2 展望 27
致谢 29
参考文献 30
1.67万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要： 图像去噪是图像增强、分割、识别等后续图像处理的必要环节，Contourlet去噪算法和基于非下采样Contourlet变换自适应阈值图像去噪方法日益受到学者的关注。本文阐述了基于多尺度多方向图像去噪算法的原理、方法和实现过程，对Contourlet和非下采样Contourlet理论做了详细讲解并对Contourlet和非下采样自适应阈值去噪算法进行了分析，在开发软件MATLAB7.0进行了仿真。本文重点分析基于非下采样Contourlet变换自适应阈值图像去噪方法。首先对噪声图像进行非下采样Contourlet变换，得到各个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值。实验表明，与Contourlet多尺度阈值去噪、Contourlet自适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR值, 减少了Gibbs现象。
关键词： Contourlet变换 非下采样Contourlet变换 图像去噪 阈值
Research of Image De-Noising Algorithm Using Adaptive Threshold Based on Non Subsampled Contourlet Transform
Abstract ：Image denoising is an essential process for image enhancement, segmentation and recognition. Recently the denoising method based on Contourlet Transform and nonsubsampled contourlet transform is becoming more and more attention by scholars. This paper describes the image denoising theory based on multi-scale and multi-directions transform, introduces the denoising method based on the wavelet and contourlet transform adaptive threshold algorithm, and stimulate in matlab7.0, the results were satisfactory. A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform (NSCT) is importantly presented. The noised image is firstly decomposed into a set of multiscale and multidirectional frequency subbands by NSCT, the threshold is adapted automatically according to the energy of subband coefficients. Comparing with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform , the simulation results show that the performance of this method is superior in psnr, meanwhile it can maintain the image edge and reduce the Gibbs phenomena.
Keywords ：Contourlet Transform onsubsampled contourlet transform Digital Image Process threshold
目 录
第一章 绪论 1
1.1 图像去噪的基本概念 1
1.2 图像去噪研究的背景、现状及其意义 2
1.3 课题研究的背景、意义及其发展 3
第二章 传统的图像去噪算法 6
2.1 基于小波分析的图像去噪 6
2.2 基于多尺度几何分析的图像去噪 8
第三章 Contourlet去噪变换方法 11
3.1 基于Contourlet的图像去噪的内容 11
3.2 基于Contourlet的图像去噪的仿真与结果 11
第四章 非下采样Contourlet变换去噪方法 18
4.1 非下采样 Contourlet 变换 18
4.1.1 非下采样 Contourlet 变换的内容 18
4.1.2 NSCT自适应阈值去噪原理 20
4.2 基于非下采样Contourlet的图像去噪的仿真与结果分析 22
4.2.1 对图像NSCT 变换去噪仿真 22
4.2.2 对图像进行NSCT变换去噪仿真结果分析 23
第五章 总结 26
5.1 结论 26
5.2 展望 27
致谢 29
参考文献 30
