It is difficult to achieve restoration of high frequency information by the traditional algorithms using an undersampled and degraded low-resolution image. Nonlinear algorithms provide a better solution to above probl...
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ISBN:
(纸本)0819445541
It is difficult to achieve restoration of high frequency information by the traditional algorithms using an undersampled and degraded low-resolution image. Nonlinear algorithms provide a better solution to above problem. As a nonlinear and real-time processing method, a MLP neural network super-resolution restoration for the undersampled and degraded low-resolution image is proposed. Experimental results demonstrate that the proposed approach can achieve super-resolution and a good restored image.
From a system level perspective, this paper presents a 128 x 128 flexible and reconfigurable Focal-Plane Analog Programmable Array Processor, which has been designed as a single chip in a 0.35 mum standard digital IP-...
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From a system level perspective, this paper presents a 128 x 128 flexible and reconfigurable Focal-Plane Analog Programmable Array Processor, which has been designed as a single chip in a 0.35 mum standard digital IP-5M CMOS technology. The core processing array has been designed to achieve high-speed of operation and large-enough accuracy (similar to7 bits) with low power consumption. The chip includes on-chip program memory to allow for the execution of complex, sequential and/or bifurcation flow imageprocessingalgorithms. It also includes the structures and circuits needed to guarantee its embedding into conventional digital hosting systems: external data interchange and control are completely digital. The chip contains close to four million transistors, 90% of them working in analog mode. The chip features up to 330 GOPs (Giga Operations per second), and uses the power supply (180 GOP/Joule) and the silicon area (3.8 GOPS/mm(2)) efficiently, and is able to maintain vGA processing throughputs of 100 Frames/s with about 10-20 basic imageprocessing tasks on each frame.
We describe a novel approach to solve a problem of window size selection for median based filtering of noisy images. The approach is based on the intersection of confidence intervals (ICI) rule and results in algorith...
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ISBN:
(纸本)0819444073
We describe a novel approach to solve a problem of window size selection for median based filtering of noisy images. The approach is based on the intersection of confidence intervals (ICI) rule and results in algorithms that are simple in implementation. The ICI rule gives the adaptive varying bandwidths and enables the algorithm to be spatially adaptive in the sense that its quality is close to that which one could achieve if the smoothness of the estimated signal were known in advance. We propose and analyze a two-stage structure for the median based adaptive filter with different use of the ICI rule. At the first stage (segmentation), the ICI rule with the median filter is applied in order to find the adaptive window size for every pixel of the image. At the second stage (filtering), the image denoising is produced by a weighted median filter with varying window sizes obtained at the first stage. Two different approaches (with a single centered window and with combined four-quadrant windows), affecting the structure of the filters, have been considered in order to form the local neighborhood of the targeted pixel. Comparison of the developed algorithm with known techniques for noise removal shows the advantage of the new adaptive window size approach, both quantitatively and visually.
We investigate the task of wide format still image manipulation and compression, within the framework of a wide format document data path. For such systems, the constraints are put on performance and cost: the use of ...
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ISBN:
(纸本)0819446408
We investigate the task of wide format still image manipulation and compression, within the framework of a wide format document data path. For such systems, the constraints are put on performance and cost: the use of data compression aims at reducing both storage cost and the transfer times, which are critical for wide format printing systems. Nevertheless, different factors reduce the overall system performance and usability, using inadequate compression algorithms for an inadequate document content - that can mix text, graphics and photographs -minimizes its global usefulness. Other factors limit its usability, as the non-compatibility of compressed data-stream with basic image transformations or the pixel encoding route mostly in a raster order, that do not allow random image access. In our article, we survey the adequation of some of the existing standards and compressed file formats, with respect to the constraints of the large format document systems.
New weight functions called filters or masks, have been designed through nonparametric Local Polynomial Approximation methods (LPA) for both, de-Noising and edge detection tasks. These new masks, are combined with the...
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ISBN:
(纸本)0819444073
New weight functions called filters or masks, have been designed through nonparametric Local Polynomial Approximation methods (LPA) for both, de-Noising and edge detection tasks. These new masks, are combined with the nearest neighborhood interpolators. The produced modified nearest neighborhood interpolation filter structures are incorporated to a new and effective statistical strategy of bandwidth (window size) selection known as the Intersection of Confidence Intervals (ICI), rendering good performance and accuracy when dealing contaminated data. Nonparametric estimation methods (among them LPA) can be considered as being the driving force for the development of bandwidth selection methods (among them ICI).
Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that speci...
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Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that specific algorithms are usually needed for each process with a complexity that cannot be implemented in vLSI systems for real time imageprocessing. MM overcome the inherent drawbacks of the linear processing based on the comparison of an initial image with some well-known geometric figures. In this paper we present the implementation of a specific processor that computes MM basic operations. Using a clock frequency of 250 MHz this processor is able to handle real time 512 X 512 pixels video images. MM allows non-linear processing of images and it is based on dilation and erosion operations using a geometric figure called structural element (SE). More complex imageprocessing can be performed using these two basic operations. In this implementation the SE of 3 X 3 pixels was chosen. 0.6 mum HGaAs standard cells technology, from vitesse Semiconductor Corporation, has been used achieving a logic level gate description with the possibility of migration to another technologies. (C) 2002 Elsevier Science Ltd. All rights reserved.
We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [R...
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We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [Recognition of topological invariants by iterative arrays, Ph.D. Thesis, MIT, 1969, p. 144] and Levialdi [Commun. ACM 15 (1) (1972) 7] independently for the purpose of shrinking 4-connected and 8-connected components of binary images in linear time, respectively. It is shown that those two independently developed algorithms are closely related and in a sense they are in a dual relation such that, for any initially given binary image and its inverted one, one algorithm produces, simultaneously, an image which is dual of the one produced by the other, step-by-step. (C) 2002 Elsevier Science B.v. All rights reserved.
This contribution describes a classification module integrated into an imageprocessing system consisting of a subsequent detection, tracking, and classification stage that extends its "knowledge" about a ce...
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This contribution describes a classification module integrated into an imageprocessing system consisting of a subsequent detection, tracking, and classification stage that extends its "knowledge" about a certain object class by autonomous in situ training. In our scenario, a classifier initially trained with front and rear views of pedestrians mainly in dark clothes subsequently extends its recognition capabilities in a first step towards lateral views of pedestrians in dark clothes, in a second step towards lateral views of pedestrians wearing both dark and bright clothes. Although supervised training algorithms are applied, at no point during the autonomous in situ training processes is an interaction with a human operator necessary;all training labels are autonomously generated by computing track-specific class assignments from time-step-specific class assignments. It is demonstrated that a significant improvement of the recognition performance with respect to new appearances, i.e., lateral views, of pedestrians, can be achieved without "forgetting" the initial front and rear views. (C) 2002 Elsevier Science B.v. All rights reserved.
Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that speci...
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Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that specific algorithms are usually needed for each process with a complexity that cannot be implemented in vLSI systems for real time imageprocessing. MM overcome the inherent drawbacks of the linear processing based on the comparison of an initial image with some well-known geometric figures. In this paper we present the implementation of a specific processor that computes MM basic operations. Using a clock frequency of 250 MHz this processor is able to handle real time 512 X 512 pixels video images. MM allows non-linear processing of images and it is based on dilation and erosion operations using a geometric figure called structural element (SE). More complex imageprocessing can be performed using these two basic operations. In this implementation the SE of 3 X 3 pixels was chosen. 0.6 mum HGaAs standard cells technology, from vitesse Semiconductor Corporation, has been used achieving a logic level gate description with the possibility of migration to another technologies. (C) 2002 Elsevier Science Ltd. All rights reserved.
Unequal loss protection with systematic Reed-Solomon codes allows reliable transmission of embedded multimedia over packet erasure channels. The design of a fast algorithm with low memory requirements for the computat...
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ISBN:
(纸本)0780376226
Unequal loss protection with systematic Reed-Solomon codes allows reliable transmission of embedded multimedia over packet erasure channels. The design of a fast algorithm with low memory requirements for the computation of an unequal loss protection solution is essential in real-time systems. Because the determination of an optimal solution is time-consuming, fast suboptimal solutions have been used. In this paper, we present a fast iterative improvement algorithm with negligible memory requirements. Experimental results for the JPEG2000, 2D, and 3D set partitioning in hierarchical trees (SPIHT) coders showed that our algorithm provided close to optimal peak signal-to-noise ratio (PSNR) performance, while its time complexity was significantly lower than that of all previously proposed algorithms.
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