Abstract
In this paper, we develop a novel linear singularity representation method using spatial K-neighbor block-extraction and Haar transform (BEH). Block-extraction provides a group of image blocks with similar (generally smooth) backgrounds but different image edge locations. An interblock Haar transform is then used to represent these differences, thus achieving a linear singularity representation. Next, we magnify the weak detailed coefficients of BEH to allow for image enhancement. Experimental results show that the proposed method achieves better image enhancement, compared to block-matching and 3D filtering (BM3D), nonsubsampled contourlet transform (NSCT), and guided image filtering.
| Original language | English |
|---|---|
| Article number | 6395147 |
| Journal | Mathematical Problems in Engineering |
| Volume | 2019 |
| DOIs | |
| Publication status | Published - 2019 Jan 1 |
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ASJC Scopus subject areas
- Mathematics(all)
- Engineering(all)
Cite this
Block-Extraction and Haar Transform Based Linear Singularity Representation for Image Enhancement. / Hou, Yingkun; Qu, Xiaobo; Liu, Guanghai; Lee, Seong Whan; Shen, Dinggang.
In: Mathematical Problems in Engineering, Vol. 2019, 6395147, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Block-Extraction and Haar Transform Based Linear Singularity Representation for Image Enhancement
AU - Hou, Yingkun
AU - Qu, Xiaobo
AU - Liu, Guanghai
AU - Lee, Seong Whan
AU - Shen, Dinggang
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In this paper, we develop a novel linear singularity representation method using spatial K-neighbor block-extraction and Haar transform (BEH). Block-extraction provides a group of image blocks with similar (generally smooth) backgrounds but different image edge locations. An interblock Haar transform is then used to represent these differences, thus achieving a linear singularity representation. Next, we magnify the weak detailed coefficients of BEH to allow for image enhancement. Experimental results show that the proposed method achieves better image enhancement, compared to block-matching and 3D filtering (BM3D), nonsubsampled contourlet transform (NSCT), and guided image filtering.
AB - In this paper, we develop a novel linear singularity representation method using spatial K-neighbor block-extraction and Haar transform (BEH). Block-extraction provides a group of image blocks with similar (generally smooth) backgrounds but different image edge locations. An interblock Haar transform is then used to represent these differences, thus achieving a linear singularity representation. Next, we magnify the weak detailed coefficients of BEH to allow for image enhancement. Experimental results show that the proposed method achieves better image enhancement, compared to block-matching and 3D filtering (BM3D), nonsubsampled contourlet transform (NSCT), and guided image filtering.
UR - http://www.scopus.com/inward/record.url?scp=85071100516&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071100516&partnerID=8YFLogxK
U2 - 10.1155/2019/6395147
DO - 10.1155/2019/6395147
M3 - Article
AN - SCOPUS:85071100516
VL - 2019
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
SN - 1024-123X
M1 - 6395147
ER -