Implementation of an Image Restoration with Block Iteration Method for Spatially Variant Blur Models
In image restoration, for spatially variant blur, block-wise iterative method have been proposed. Block-wise iterative method is based on the assumption that the blur approximates to spatially invariant in a small region of the blurred images. These appro
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Automation and Energy Technology Institute, Sunmoon University, Asan, South Korea [email protected] Division of Mechanics and ICT Convergence Engineering, Sunmoon University, Asan, South Korea {kuks2309,mcp94lee}@sunmoon.ac.kr
Abstract. In image restoration, for spatially variant blur, block-wise iterative method have been proposed. Block-wise iterative method is based on the assumption that the blur approximates to spatially invariant in a small region of the blurred images. These approaches show approximation errors and block artifacts. In this work, we suggest to use block iterative method without approximates to spatially invariant blur considering arbitrary shaped blocks related to shapes of blur models. We can reduce the approximation errors and block artifacts with high speed of iteration convergence. This proposed image restoration method can reduce the computational efforts and is useful to embedded system such as mobile phone and embedded vision system. Keywords: Spatially variant blur
Block selection Block iteration method
1 Introduction Spatially variant deblurring problem is computationally infeasible, because fast Fourier transform based method cannot be used [1]. To address this difficulty, block-wise iterative method have been proposed [2]. Sectioning method decompose the blurred image into several blocks equivalently, and deblur each sub-images separately using its approximate spatially invariant blur, and then combines those block-images to form the final image [3]. This approaches, however, suffer from approximation errors and block artifacts. In this work, for the spatially variant deblurring, we suggest to use the spatially-variant blur model itself in a small region. We propose the Separate block iteration method (SBI) and the Interlaced block iteration method (IBI). These two methods are based on Richardson-Lucy method. The Separated block iteration method (SBI) is same to the sectioning method [3], but the separated block iteration method (SBI) use the spatially-variant blur model itself. We propose to use the arbitrary block shapes which is related to the blur models. For example, we consider the rectangular blocks for Gaussian blur and the diagonal blocks for Motion blur. For accelerating speed of convergence, Interlaced block © Springer Nature Singapore Pte Ltd. 2017 J.J. (Jong Hyuk) Park et al. (eds.), Advances in Computer Science and Ubiquitous Computing, Lecture Notes in Electrical Engineering 421, DOI 10.1007/978-981-10-3023-9_65
Implementation of an Image Restoration with Block Iteration Method
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iteration method (IBI) uses a small portion of observed data sequentially in each iteration. As iteration goes, we choose whole data evenly. In simulation study, as spatially variant blur model, we consider the Gaussian blur model and the diagonal blur model. Our proposed method have many advantages. Real-time image reconstruction using small amount of pixels, even more precise images without development of devices is possible.
2 Definition and Background 2.1
Image Deblurrin
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