An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, wh...An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, which become increasingly tighter for the matching criteria, the method tries to successively terminate unnecessary computations of the matching criteria between the reference block in one image and the ineligible candidate blocks in another image.It also eliminates the ineligible blocks as early as possible, while ensuring the optimal disparity of each pixel.Also, the proposed method can further speed up the elimination of ineligible candidate blocks by efficiently using the continuous constraint of disparity to predict the initial disparity of each pixel.The performance of the new algorithm is evaluated by carrying out a theoretical analysis, and by comparing its performance with the disparity estimation method based on the standard block matching.Simulated results demonstrate that the proposed algorithm achieves a computational cost reduction of over 50.5% in comparision with the standard block matching method.展开更多
Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based ...Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.展开更多
Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel...Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference （RBSAD） metric for calculating matching error and conversion to full resolution sum of absolute difference （SAD） metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthe- sized using Xilinx Synthesis Tools （XST）, where the ME designs based on reduced bit （RB） algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.展开更多
基金supported by the Opening Project of State Key Laboratory for Manufacturing Systems EngineeringFoundation for Youth Teacher of School of Mechanical Engineering, Xi’an Jiaotong University Brain Korea 21(BK21) Program of Ministry of Education and Human Resources Development
文摘An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, which become increasingly tighter for the matching criteria, the method tries to successively terminate unnecessary computations of the matching criteria between the reference block in one image and the ineligible candidate blocks in another image.It also eliminates the ineligible blocks as early as possible, while ensuring the optimal disparity of each pixel.Also, the proposed method can further speed up the elimination of ineligible candidate blocks by efficiently using the continuous constraint of disparity to predict the initial disparity of each pixel.The performance of the new algorithm is evaluated by carrying out a theoretical analysis, and by comparing its performance with the disparity estimation method based on the standard block matching.Simulated results demonstrate that the proposed algorithm achieves a computational cost reduction of over 50.5% in comparision with the standard block matching method.
基金supported by the National Natural Science Foundation of China(6110118561302145)
文摘Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.
文摘Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference （RBSAD） metric for calculating matching error and conversion to full resolution sum of absolute difference （SAD） metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthe- sized using Xilinx Synthesis Tools （XST）, where the ME designs based on reduced bit （RB） algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.
