| 引用本文: | 石翠萍,张钧萍,张晔.一种新的基于混合变换的图像稀疏表示[J].哈尔滨工业大学学报,2014,46(9):36.DOI:10.11918/j.issn.0367-6234.2014.09.007 |
| SHI Cuiping,ZHANG Junping,ZHANG Ye.A novel image sparse representation based on the hybrid transform[J].Journal of Harbin Institute of Technology,2014,46(9):36.DOI:10.11918/j.issn.0367-6234.2014.09.007 |
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| 摘要: |
| Tetrolet变换对图像中边缘和纹理的稀疏逼近性能远远高于小波变换,对细节丰富的图像具有明显优势,但其对平滑图像的逼近性能却不如小波变换．针对这一问题,本文提出了具有一定普适性的图像稀疏方法．首先,对图像进行小波变换,采用p-fold抽取滤波器对各子带进行多相分解,对分解结果进行主成分变换,并对两次能量聚集后的图像进行低频稀疏逼近；然后,根据前面结果生成细节图像,采用Tetrolet变换进行高频稀疏逼近．实验表明,在相同条件下,无论是客观质量还是主观质量,该方法均优于单一的小波变换和Tetrolet变换,证实了本文方法的有效性． |
| 关键词: 图像稀疏逼近 Tetrolet变换 小波变换 多相分解 |
| DOI：10.11918/j.issn.0367-6234.2014.09.007 |
| 分类号:TP751.1 |
| 基金项目:国家自然科学基金资助项目(61271348);黑龙江省教育厅资助项目(12521614);齐齐哈尔大学青年教师科研启动项目(2011k-M11). |
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| A novel image sparse representation based on the hybrid transform |
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SHI Cuiping1,2, ZHANG Junping1, ZHANG Ye1
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(1.School of Electronic and Information Engineering, Harbin Institute of Technology, 150001 Harbin, China; 2.School of Communication and Electronic Engineering, 161000 Qiqihaer, Heilongjiang, China)
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| Abstract: |
| The sparse approximation performance of tetrolet transform to the edge and texture of image is much higher than wavelet transform, which makes it suitable for those images that rich in details. However, for the smooth images, its sparse approximation performance is weaker than wavelet transform. Focus on the problem, a novel sparse approximation method that is of some generality is proposed. First, the wavelet transform is conducted to the image, and the polyphase decomposition for each sub-band is operated using p-fold filter and some components are generated, then the PCA is applied to those components. Following, the sparse approximation is conducted to the image after two energy concentration. Secondly, the high-frequency image can be obtained based on the results above, then the tetrolet transform is applied to sparse it. Experimental result shows that, under the same condition, the quality of the reconstructed image obtained by the proposed method is better than that obtained by the wavelet transform and the tetrolet transform, either the subjective or objective quality, which indicates the effectiveness of the proposed method. |
| Key words: image sparse approximation tetrolet transform wavelet transform polyphase decomposition |
