Flexible Hardware-Based Stereo Matching

Ambrosch, Kristian; Kubinger, Wilfried; Humenberger, Martin; Steininger, Andreas

doi:10.1155/2008/386059

Cited by 20 publications

(21 citation statements)

References 9 publications

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“…The intensity difference between both blocks is measured by several methods such as sum of absolute difference (SAD), mean-squared error (MSE), and least square error (LSE). In our present work, we have used the SAD measure as the minimum distance computation metric because this measure needs less hardware compared to other distortion measurement methods [2]. Compression is achieved when a larger part of image is represented by a smaller part of image.…”

Section: Fundamentals Of Fractal Image Compressionmentioning

confidence: 99%

Low-Delay Parallel Architecture for Fractal Image Compression

Panigrahy

Chakrabarti

Dhar

2015

Circuits Syst Signal Process

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This paper presents an efficient hardware architecture for implementing fractal image compression (FIC) algorithm aimed toward image compression with improved encoding speed. The proposed architecture follows the full-search-based FIC scheme. Parallel processing has been effectively used in the present work to achieve the goal of reducing the time complexity of the encoder. This architecture requires a total of 2n + 2 clock cycles for executing the set of operations consisting of fetching the pixels, calculating the mean of range and domain blocks and doing their mapping, computing the error, and storing the fractal parameter in a memory with n number of pixels in the range block. Further, this architecture does not make use of any preprocessing operations as specified in literature and utilizes the benefits of isometric transformation without requiring additional cycles for every single matching operation. Effective application of isometric transformation has also led to memory reduction of nearly 67 %. Again, in the present work, the use of multipliers has been avoided to save the chip area, to reduce hardware complexity, and to enhance the encoding speed. The operation of transforming contracted domain block with a zero-mean domain block has facilitated relatively fast convergence at the decoder. PSNR above 30dB for a range block of size 4 × 4 has been achieved by the proposed architecture, which is comparable to that realizable by other architectures. The proposed design has been coded in Verilog HDL, has been implemented in Xilinx Virtex-5 FPGA, and operates at a clock frequency of 75.52 MHz.

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Section: Fundamentals Of Fractal Image Compressionmentioning

confidence: 99%

Low-Delay Parallel Architecture for Fractal Image Compression

Panigrahy

Chakrabarti

Dhar

2015

Circuits Syst Signal Process

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“…Woodfill et al [37] described an ASIC design called DeepSea which enables the processing of 512 × 480 at a disparity range of 52 pixels, a block size of 7 × 7, and a high frame rate of 200 fps. The technique for implementing a flexible block size, disparity range and frame rate was proposed in [38]. The impact of using different similarity measures as SAD, rank, and census transform was also presented.…”

Section: Related Studiesmentioning

confidence: 99%

Real-time stereo vision system using adaptive weight cost aggregation approach

Ding

Liu

Zhou

et al. 2011

J Image Video Proc.

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Many vision applications require high-accuracy dense disparity maps in real time. Due to the complexity of the matching process, most real-time stereo applications rely on local algorithms in the disparity computation. These local algorithms generally suffer from matching ambiguities as it is difficult to find appropriate support for each pixel. Recent research shows that algorithms using adaptive cost aggregation approach greatly improve the quality of disparity map. Unfortunately, although these improvements are excellent, they are obtained at the expense of high computational. This article presents a hardware implementation for speeding up these methods. With hardware friendly approximation, we demonstrate the feasibility of implementing this expensive computational task on hardware to achieve real-time performance. The entire stereo vision system, includes rectification, stereo matching, and disparity refinement, is realized using a single field programmable gate array. The highly parallelized pipeline structure makes system be capable to achieve 51 frames per second for 640 × 480 stereo images. Finally, the success of accuracy improvement is demonstrated on the Middlebury dataset, as well as tests on real scene.

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“…In all the considered works [1][2][3][4][5][6][7][8][9] the optical scheme of stereoscopic system which is the basis of the geometric scheme construction was not studied. For example, in works [1][2][3][4][5] the geometric model of simple stereoscopic system provided by space coordinate calculation formulas is presented.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in works [1][2][3][4][5] the geometric model of simple stereoscopic system provided by space coordinate calculation formulas is presented. However, these formulas are given only in geometric form without using optical scheme, their pixel interpretation is not provided, and there is no substantia-tion of the geometric scheme construction.…”

Section: Introductionmentioning

confidence: 99%

“…Below we provide the strict proving that the formula of the depth coordinate Z di ers from the similar formula presented in the work [3]. The formulas considered in the works [1][2][3][4][5] have geometric representation and can not have practical application for real stereoscopic systems, since the real data of the obtained images is presented in the pixel form. In the work [5] it is indicated that the center of global coordinates coincides with the image center of the left camera.…”

Section: Introductionmentioning

confidence: 99%

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Calculation of 3D Coordinates of a Point on the Basis of a Stereoscopic System

Mussabayev

Kalimoldayev²,

Amirgaliyev³

et al. 2018

Open Engineering

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Abstract:The solution of three-dimensional (3D) coordinate calculation task for a material point is considered. Two at images (a stereopair) which correspond to the left and to the right viewpoints of a 3D scene are used for this purpose. The stereopair is obtained using two cameras with parallel optical axes. The analytical formulas for calculating 3D coordinates of a material point in the scene were obtained on the basis of analysis of the stereoscopic system optical and geometrical schemes. The detailed presentation of the algorithmic and hardware realization of the given method was discussed with the the practical. The practical module was recommended for the determination of the optical system unknown parameters. The series of experimental investigations were conducted for veri cation of theoretical results. During these experiments the minor inaccuracies were occurred by space distortions in the optical system and by it discrecity. While using the high quality stereoscopic system, the existing calculation inaccuracy enables to apply the given method for the wide range of practical tasks.

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Flexible Hardware-Based Stereo Matching

Cited by 20 publications

References 9 publications

Low-Delay Parallel Architecture for Fractal Image Compression

Low-Delay Parallel Architecture for Fractal Image Compression

Real-time stereo vision system using adaptive weight cost aggregation approach

Calculation of 3D Coordinates of a Point on the Basis of a Stereoscopic System

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