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A major problem related to the block-based discrete cosine transform techniques is that the decoded images, especially at very low bit rates, exhibit highly noticeable blocking artifacts near the block boundaries. In this paper, an fuzzy de-blocking algorithm based on ICM filter is proposed. Based on some characteristics of human visual system, this algorithm applies ICM filter to current pixel by...
In order to classify the pavement cracks in the pavement crack images, a new chain code based classification method are proposed. In this method, the preprocessing of the crack images is used to remove the unwanted object, noise and enhance the cracks. Secondly, the max entropy thresholding method is used to get the binary pavement crack images. After this, the morphological filtering operation, especially...
Since the large diffusion of digital camera and mobile devices with embedded camera and flashgun, the red-eyes artifacts have de-facto become a critical problem. The technique herein described makes use of three main steps to identify and remove red-eyes. First, red eyes candidates are extracted from the input image by using an image filtering pipeline. A set of classifiers is then learned on gray...
Several techniques have been proposed so far in order to perform faint compact source detection in wide field interferometric radio images. However, all these methods can easily miss some detections or obtain a high number of false positive detections due to the low intensity of the sources, the noise ratio, and the interferometric patterns present in the images. In this paper we present a novel strategy...
Obtaining high quality images in MR is desirable not only for accurate visual assessment but also for automatic processing to extract clinically relevant parameters. Filtering-based techniques are extremely useful for reducing artifacts caused due to under sampling of k-space (to reduce scan time). The recently proposed Non-Local Means (NLM) filtering method offers a promising means to denoise images...
Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by micro aneurysm (MA). Although some algorithms have been developed, the accurate detection of MA in color retinal images is still a challenging problem. In this paper we propose a new method to detect MA based on Sparse Representation...
This paper shows a novel application of the diffusion tensor for anisotropic image processing. The designed system aims at spotting and localizing injection points on a population of adherent cells lying on a Petri's dish. The overall procedure is described including pre-filtering, ridge enhancement, cell segmentation, shape analysis and injection point detection. The anisotropic contour completion...
This papers presents a weakly supervised method to simultaneously address object localization and recognition problems. Unlike prior work using exhaustive search methods such as sliding windows, we propose to learn category and image-specific visual words in image collections by extracting discriminating feature information via two different types of support vector machines: the standard L2-regularized...
In this paper we present a scene analysis technique with subpixel filtering based on dense coded light fields. Our technique computes alignment and optically projects analysis filters to local surfaces within the extent of a camera pixel. The resolution gain depends on the local light field density not on the point spread function of the camera optics. An initial structured light sequence is used...
Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for computing the NL-means denoising filter, image patches can be favourably replaced by a vector of spatial derivatives (local jet), to calculate the similarity between pixels. First, we present the basic, limited range implementation, and compare it with the original NL-means....
This paper extends a recent image-dependent regularisation approach introduced in aiming at edge-preserving smoothing. For that purpose, geodesic distances equipped with a Riemannian metric need to be estimated in local neighbourhoods. By deriving an appropriate metric from the gradient structure tensor, the associated geodesic paths are constrained to follow salient features in images. Following,...
We propose a level set based framework to segment textured images. The snake deforms in the image domain in searching for object boundaries by minimizing an energy functional, which is defined based on dynamically selected local distribution of orientation invariant features. We also explore the user initialization to simplify the segmentation and improve accuracy. Experimental results on both synthetic...
In this paper, we present a new method to enhance depth images captured by a time-of-flight (TOF) depth sensor spatially and temporally. In practice, depth images obtained from TOF depth sensors have critical problems, such as optical noise existence, unmatched boundaries, and temporal inconsistency. In this work, we improve depth quality by performing a newly-designed joint bilateral filtering, color...
Back-to-front, show-through, or bleeding are the names given to the interference that appears whenever one writes or prints on both sides of translucent paper. Such interference degrades image binarization and document transcription via OCR. The technical literature presents several algorithms to remove the back-to-front noise, but no algorithm is good enough in all cases. This article presents a...
For removing salt and pepper noise from corrupted images we are using so many algorithms. In this paper, a robust statistical based median filter is introduced to remove salt and pepper noise. The function of the algorithm is to detect the corrupted pixel first since the impulse noise only affect certain pixels in the image and the remaining pixels are uncorrupted. The corrupted pixels are replaced...
Image processing and recognition technologies are becoming increasingly important. Automatic construction methods for image transformation algorithms proposed to date approximate adequate image transformation from original images to their target images using a combination of several known image processing filters by evolutionary computation techniques. In this paper, we introduce the adaptive image...
H.264/MPEG-4 AVC uses motion prediction with fractional-pixel precision to reduce the temporal redundancy that often exists in a video signal. Previously, it has been shown that Adaptive Interpolation Filter (AIF) methods can significantly improve coding performance compared to the fixed interpolation filters used by existing codecs by adaptively tuning the motion interpolation filters to the video...
In this paper a new filtering framework for colour image sequences corrupted by random impulse noise is introduced. The proposed method consists of three successive filtering steps in order to find a good trade-off between detail preservation and noise removal. One hard filtering step, that should remove all the noise at once, would namely also remove a considerable amount of details. In the different...
Filtering of raster map images or more general class of palette-indexed images can be considered as a discrete denoising problem with finite color output. Statistical features of local context are used to avoid damages of some specific but frequently occurring contexts caused by conventional filters. Several context-based approaches have been developed using either fixed context templates or context...
In this paper, we propose a unified loop filter for high-performance video coding, which suppresses the quantization noise optimally and improves the objective and subjective quality of the reconstructed picture simultaneously. The proposed filter unifies nonlinear enhancement filter (for removing blocking and ringing artifacts) and linear restoration filter (for improving coding efficiency) within...
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