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In this paper, an adaptive blind image restoration algorithm is proposed. According to the feature that the certain blur may lead to the specific component distortion in the cepstral domain, we develop an automatic algorithm using Fourier-Mellin transform to classify and identify the point spread function (PSF) with cepstrum: for the usual types of blur,(More)
Traditional Hough transform can not locate the accurate position of line segments. It is too complex in practical liner target detection based on improved Radon. Both transforms is used associated in this paper in order to recognize the attitude of multi-targets as line segments accurately with an acceptable complexity in calculation. A new method called(More)
—H.264/AVC intra prediction employs the rate distortion optimization (RDO) technique to get to the best encoding performance. But exhaustively searching all candidate modes dramatically increases the computational complexity for encoding. In order to reduce the computational complexity, in this work, we proposed a low complexity mode decision algorithm(More)
An image is often corrupted by noise in its acquisition or transmission. The goal of denoising is to remove the noise while retaining as much as possible the important signal features. In this paper, we propose a doubly local Wiener filtering method using adaptive directional windows and Mean Shift algorithm, in which the Mean Shift algorithm is first used(More)
Detection based on Hough Transform is a good way frequently employed to detect straight-line targets, but it bears problems as difficulty in selecting an appropriate threshold coefficient and target misjudgment. To solve those technical problems mentioned above, this paper proposes a novel algorithm based on Hough Transform and Mean Shift Multi-Scale(More)
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