Double-regularization approach for blind restoration of multichannel imagery

Chow, Tommy W. S.; Li, Xiaodong; Ng, K.T.

doi:10.1109/81.948435

Cited by 17 publications

(27 citation statements)

References 13 publications

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“…The linear color image degradation processes are commonly modeled by [2], [4] (1) = is strongly correlated. We denote that the low-pass filters a lp (x) and a lp (y), and the high-pass filters a hp (x) and a hp (y) are the analysis filter banks performing a redundant discrete wavelet transform (RDWT) in the horizontal (x) and vertical (y) directions, respectively.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Therefore, we extend the method to address the three-channel SISO model given in Fig.2. The proposed cost function is given as follows: (4) , , ( , , , , , ) ( , ) …”

Section: Development Of Wavelet-based Deconvolution Schemementioning

confidence: 99%

“…Chow et al [4] extend the framework of single-input single-output (SISO) model in grayscale image deconvolution to color image deconvolution. A three-dimensional (3-D) Laplacian operator is employed to regularize the images.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Blind color image deconvolution based on wavelet decomposition

Yap

Chen

et al. 2005

IEEE International Conference on Image Processing 2005

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This paper presents a new framework to address blind color image deconvolution based on wavelet decomposition. Blind color image deconvolution is a challenging problem due to the lack of information available. Conventional methods based on single-input single-output (SISO) model experience significant color artifacts in the restored images. On the other hand, there are limitations on the practicality of using multi-input multioutput (MIMO) model in solving this problem as the color channels are usually highly correlated. In view of this, this paper proposes a new framework to solve blind color image deconvolution by first decomposing the color channels into wavelet subbands, and performing image deconvolution using a combination of SISO and single-input multi-output (SIMO) models. Experimental results show that the proposed method is able to achieve satisfactory restored images.

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Section: Problem Formulationmentioning

confidence: 99%

“…Therefore, we extend the method to address the three-channel SISO model given in Fig.2. The proposed cost function is given as follows: (4) , , ( , , , , , ) ( , ) …”

Section: Development Of Wavelet-based Deconvolution Schemementioning

confidence: 99%

See 1 more Smart Citation

Blind color image deconvolution based on wavelet decomposition

Yap

Chen

et al. 2005

IEEE International Conference on Image Processing 2005

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“…In many applications such as super-resolution and microscopy imaging, multiple degraded images of a single scene become available while the original image and the blurs remain unknown. There are some rather successful works on development of multispectral restoration, which exploit the benefits of single-channel restoration techniques [2], [10], [11].…”

Section: Introductionmentioning

confidence: 99%

“…A promising attempt has been made by utilizing the multispectral eigenvector-based method (EVAM) as a regularization term in the framework of TV [10]. A direct extension of DR has also been applied successfully in color image restoration [11].…”

Section: Introductionmentioning

confidence: 99%

Double regularization approach to iterative blind multispectral image restoration

Chen

Changjie

2007

SPIE Proceedings

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In this paper, we present a new iterative blind multispectral image restoration algorithm based on double regularization (DR). The motivation for DR when applied to multispectral restoration lies in its effectiveness towards edge preservation in joint blur identification and image restoration. With consideration for both the intra-and inter-channel blurring function in the multiple-input multiple-output (MIMO) systems, an alternating minimization (AM) procedure with conjugate gradient optimization (CGO) scheme is formulated to implement restoration iteratively. The derivation of DR optimization shows that optimal restoration result can be achieved even when the MIMO systems suffer from interchannel interference. Experimental results show that it is effective in performing blind mutichannel restoration when applied to color images.

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A Novel Blind Image Restoration Algorithm Using A SVR-Based Noise Reduction Technique

Xia

Bin

2013

Advances in Intelligent Systems and Computing

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Double-regularization approach for blind restoration of multichannel imagery

Cited by 17 publications

References 13 publications

Blind color image deconvolution based on wavelet decomposition

Blind color image deconvolution based on wavelet decomposition

Double regularization approach to iterative blind multispectral image restoration

A Novel Blind Image Restoration Algorithm Using A SVR-Based Noise Reduction Technique

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