• Journal of Broadcast Engineering
• /
• v.10 no.2
• /
• pp.238-246
• /
• 2005

This paper proposes an iterative high-resolution image interpolation algorithm using spatially adaptive constraints and regularization functional. The proposed algorithm adapts adaptive constraints according to the direction of..edges in an image, and can restore high-resolution image by optimizing regularization functional at each iteration, which is suitable for edge directional regularization. The proposed algorithm outperforms the conventional adaptive interpolation methods as well as non-adaptive ones, which not only can restore high frequency components, but also effectively reduce undesirable effects such as noise. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.6
• /
• pp.26-35
• /
• 2009

In this paper, we present morphology-based step region extraction and regularized iterative point-spread-function (PSF) estimation methods. The proposed PSF estimation method uses canny edge detector to extract the edge of the input image. We extract feasible vertical and horizontal edges using morphology analysis, such as the hit-or-miss transform. Given extracted edges we estimate the optimal step-response using flattening and normalization processes. The PSF is finally characterized by solving the equation which relates the optimal step response and the 2D isotropic PSF. We shows the restored image by the estimated PSF. The proposed algorithm can be applied a fully digital auto-focusing system without using mechanical focusing parts.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.4
• /
• pp.39-44
• /
• 2004

The three-dimensional (3D) wavelet transform with motion compensation is suitable for very high quality video coding due to both spatial and temporal decorrelations. However, it still suffers from image degradation such as ringing artifact and afterimage because of the loss of high frequency components by quantization. This paper proposes an iterative regularized enhancement of the motion-compensated 3D wavelet coded video. We also propose the adaptive implementation of the constraints for the regularization. It selectively suppresses the high frequency component along only the corresponding edge direction.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.8
• /
• pp.1803-1813
• /
• 1997

The goal of image restoration is to remove the degradations in a way that the resrored image will best approximate the original image. This can be done by the iterative regularized image restoration method. In any iterative image restoration algorithm, using a "better" termination rule results in both "better" quality of ther restored image and "less" computation, and hence, "faster" and "simp;er" practical system. Therefore, finding a better termmination rule for an iterative image restoration algorithm has been an interesting and improtant question for many researchers in the iterative image restoration. In these reasons, the new termination rule using the estimated distance between the original image and the restored image is proposed inthis paper. Noise suppression parameter(NSP) and the rule for estimating NSP with the noise variance are also proposed. The experimental results shows that the proposed termination rule is superior to the conventional methods.