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A geometric features-based filtering technique, named as the adaptive geometric features based filtering technique (AGFF), is presented for removal of impulse noise in corrupted color images. In contrast with the traditional noise detection techniques where only 1D statistical information is used for noise detection and estimation, a novel noise detection(More)
This paper presents a feature-based approach for fast face recognition. A novel shape-based automatic reference control point and feature extraction technique is proposed for face representation, whereby the difference between two faces is measured by a set of extracted features, and 3-D features from a set of 2-D images are used for face template(More)
This paper introduces a new hybrid image enhancement approach driven by both global and local processes on luminance and chrominance components of the image. This approach, based on the parameter-controlled virtual histogram distribution method, can enhance simultaneously the overall contrast and the sharpness of an image. The approach also increases the(More)
An adaptive geometric features based filtering (AGFF) technique with a low computational complexity is proposed for removal of impulse noise in corrupted color images. The effective and efficient detection is based on geometric characteristics and features of the corrupted pixel and/or the pixel region. A progressive restoration mechanism is devised using(More)
In this paper, we present a feature-based approach to fast face recognition. A novel shape based automatic reference landmark and feature extraction technique is proposed for face representation. The difference between two faces is measured by a set of the extracted features and three-dimensional (3-D) features are used for a face template registration.(More)
This paper introduces a novel image enhancement methodology driven by both global and local processes. This methodology, based on the parameters controlled hybrid approach which integrates the advantages of point operations with local enhancement techniques, can enhance, simultaneously, the overall contrast and the sharpness of an image and increase,(More)
Motion estimation is an important component for video processing and compression. A fast spatiotemporal statistical information based motion estimation technique is proposed in this paper. It uses the spatiotemporal correlation in the image sequence to detect and to estimate global motion, based which a block matching approach is applied for more accurate(More)
We propose an adaptive surveillance video noise filter (ASVNF) using models for marginal distributions of wavelet coefficients. In order to suppress mixture Poisson-Gaussian noise for surveillance video, the wavelet domain based denoising function in the ASVNF adapts its output to the local spatial video structure and the property of the video noise. Based(More)