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We present a simple method for image denoising called power iteration denoising (PID). PID finds a low dimensional embedding of the image data using a truncated power iteration on a normalized pair-wise similarity matrix generated from the image. This embedding turns out to be an effective denoising algorithm outperforming the widely used non-local means algorithm. We apply this method to the denoising...
In this paper, we present an algorithm to remove high-frequent texture and detail from images without destroying high-level image structure or introducing artificial edges. While based on the same general framework, this “image simplification” filter differs from noise filtering methods such as bilateral filtering by its frequency-selectivity and edge awareness. Applications include artistic filtering...
The fusion of images is the process of combining two or more images into a single image retaining important features from each. Image fusion is an important technique especially in nondestructive method of testing [1 - 3] wherein no damage is done to the material being tested. There are two categories of image fusion, one being fusion of images from the same sensor and the other being multi - sensor...
A novel technique is presented to detect and remove the salt and pepper noise in digital color images. The algorithm is proposed for detection of noisy pixel, edges and noise free pixels by utilizing basic property of salt and pepper noise. Each pixel is treated according whether it is edge pixel, noisy pixel or pixel from smooth region etc. Noisy pixel are replaced with median of neighborhood of...
Multiplicative speckle noise is always present in synthetic aperture sonar (SAS) images, which is due to the coherent nature of scattering phenomena. Many methods that reduce speckle noise while preserving texture and detail have been developed for SAR and presented in the literature. In this paper, some speckle reduction techniques from SAR images are adapted and applied to SAS high resolution images...
The most annoying artifacts in image deconvolution are ringing and amplified noise. These artifacts can be reduced significantly by regularization using the Maximum a Posteriori (MAP) method that exploits not only the likelihood but also the image prior in image deconvolution. Although ringing and noise can be reduced significantly with strong regularization, image details are also reduced, so the...
In this paper, we present a novel Frobenius Norm filter, which is a spatially selective noise filtration technique in the wavelet subband domain. Impulse pixels located in the middle of large noise blotches can also be properly detected and filtered by our method. We have applied comparative Frobenius Norm under a given window set and pixel connectivity for removal of impulse noise. The Frobenius...
MODIS has wide spectral range and spatial coverage, as well as the continuous coverage MODIS will provide over time, and observes the Earth as a unified nature, which is necessary for multidisciplinary studies of land, ocean, atmospheric processes and so on, at the same time, it provide us the global data for at least 15 years. All of these characters made the great use of MODIS data. Today the data...
In this paper, an adaptive approach of bilateral filtering is introduced for the despeckling of medical ultrasound images. The range parameter is estimated from intensity homogeneity measurements. For each pixel, the measurements are carried out utilizing its local neighbors considering different directions. The range parameter is then estimated from the variance of the most homogeneous blocks and...
Wavelet transform has been successfully used in many applications such as image compression, image denoising, and computer vision. Recently, the research of image denoising focused on developing some new method which can represent the edge of image more efficiently. Ridgelets is a new system of representations, which deals effectively with line singularities in 2-D. In this paper, a simple algorithm...
In this paper a novel algorithm, called Counterpoint Harmony Search (CHS), is presented for the simultaneous denoising and deconvolution of binary images. No prior information about the noise or blur shape and size is required, which makes so called blind decon-volution of binary images possible using CHS. CHS is based on the Harmony Search algorithm and inspired by the island model parallel genetic...
The objective of this work is to evaluate the performance of a set of despeckle filters for Optical Coherence Tomography (OCT) of the skin. The six filters are based on local statistics, median filtering, pixel homogeneity, geometric filtering and transformed domain homomorphic filtering. The results of this study suggest that geometric filtering algorithm outperforms other candidate methods, and...
This paper presents an algorithm to extract the region of interest (ROI) from the palm print image of the Hong Kong PolyU large-scale palm print database (version 2). Competitive coding method is used for feature extraction. Coding based methods are among the most promising palm print recognition methods because of their small feature size, fast matching speed, and high verification accuracy. Competitive...
An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more...
This paper describes the ICFHR 2010 Contest for quantitative evaluation of binarization algorithms. These algorithm are applied to synthetic images of modern pdf documents with noise from historical documents. Today, many scientists work on the binarization task and many algorithms have been proposed. However, the selection of the most appropriate one is not a simple procedure. The evaluation of these...
In this paper, a new noise removal method for color images is described. In the proposed method, first, a tentative output image in which noise is almost perfectly removed is obtained using the iterative robust switching vector median-based vector ε-filter. Then, the residual components between the input and tentative output images are calculated, and image components constitute edges, corner, and...
Vessel segmentation is very important in an automatic screening system for fundus images. Vessels are often segmented and removed from retinal images before the other residual lesions are detected. Incomplete vessel removal usually causes a false positive in lesion detection, especially for Microaneurysms detection. Segmenting vessels in spatial image domain makes miss detection due to non illumination...
In this paper we propose a new algorithm to reduce the impulse noises in images. It contains two separated steps: impulse noise detect step and filter step. In impulse noise detect step we use the fuzzy gradient method with new fuzzy rules to distinguish the noise pixels and edge pixels; and filter step employs a novel adaptive median filter whose size is controlled by the number of interesting pixels...
The traditional Canny edge detector is designed to detect the edges of gray image, the color image must be converted to gray image, this method only uses the luminance information of color image, and don't take into account the chroma information, therefore, it misses some edges. In this paper, an improved Canny edge detector against impulsive noise based on CIELAB space is proposed, the color image...
A new type of digital filter for removing impulsive noise from color images is proposed using interactive evolutionary computing. This filter is realized as a rule-based system with interpolation technique considering the correlation among color components. This filter first detects the pixels on which impulsive noise is added on each RGB channel, based on the rules concerning the peculiarity of the...
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