In this study, a fast blockmatching search algorithm based on blocks’ descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarch...
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In this study, a fast blockmatching search algorithm based on blocks’ descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the compared blocks is achieved. Instead of pixels-wise comparisons a set of hierarchal similarity comparisons between few descriptors of the compared blocks is done. The computations of blocks descriptors have linear complexity, O(n) and small number of involved similarity comparisons is required. As final stage, the selected blocks as the best similar blocks according to their descriptors are only pushed to pixel-wise blocks comparison stage. The performance of the proposed system was tested for both cases: (i) without using prediction for assessing the initial motion vector and (ii) with using prediction that based on the determined motion vectors of already scanned neighbor blocks. The test results indicated that the introduced method for both cases (without/ with prediction) can lead to promising results in terms of time and error level; because there is reduction in search time and error level parameters in comparison with exhaustive search and three step search (TSS) algorithms.
To significantly reduce the number of block-matching (BM) processes in motion vector estimation for HDTV, we have developed an extremely fast blockmatching (BM) algorithm that we call a "Stick-Shaped Window Sear...
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ISBN:
(纸本)9781424458981
To significantly reduce the number of block-matching (BM) processes in motion vector estimation for HDTV, we have developed an extremely fast blockmatching (BM) algorithm that we call a "Stick-Shaped Window Search (SSWS)" BM algorithm for H.264/AVC. The algorithm consists of three steps: (1) sub-sampling BM in a reduced number of stick-shaped windows, (2) alternate eight-direction sub-sampling BM, and (3) cyclic small-diamond BM. For HDTV the algorithm not only improves full search (FS) processing speed by a factor of up to 2,716, but also that of a simplified unsymmetrical-cross multi-hexagon-grid search (S-UMHS) by a factor of up to 7.87, while achieving the same visual quality as that of FS.
This paper focuses on the disparity-compensated stereoscopic image coding. Such approach takes advantage of the existing redundancy between the two views as they are intended to render the visual impression of a 3D-sc...
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ISBN:
(纸本)9788362065363
This paper focuses on the disparity-compensated stereoscopic image coding. Such approach takes advantage of the existing redundancy between the two views as they are intended to render the visual impression of a 3D-scene, in which inter-view object displacements are understood as depth-related information. The classical approach is based on blockmatching (BM) algorithm, yielding a disparity map with which the predicted image is most similar to its original version. Then, with no modification of the disparity map, the residual image is encoded, yielding a refinement added to the predicted image. The proposed approach, first, improves all the possible predicted images taking into account this refinement, and then, estimates the disparity map as the one with which the predicted image resembles most that same view. Despite the significant increase in the numerical complexity, the substantial improved performance in terms of Peak-Signal to Noise-Ratio (PSNR) of this new approach is evidence of ongoing progress in this field of research.
作者：
Paramkusam, A. V.Reddy, V. S. K.Andhra Univ
Welf Inst Sci Technol & Management Elect & Commun Visakhapatnam Andhra Pradesh India JNTUH
Sri Malla Reddy Coll Engn & Technol Elect & Commun Hyderabad Andhra Pradesh India
An efficient fast full-search block-matchingalgorithm is presented that uses the sum of squared difference (SSD) criterion. The efficiency of this algorithm mainly depends on the homogeneity regions of images in the ...
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ISBN:
(纸本)9781457711091
An efficient fast full-search block-matchingalgorithm is presented that uses the sum of squared difference (SSD) criterion. The efficiency of this algorithm mainly depends on the homogeneity regions of images in the video. If the blocks having small variance values are more in current frame then this algorithm takes far fewer computations for best block searching. The proposed algorithm is executed on a personal computer with 2.53-GHz CPU. Since the CPU takes fewer clock cycles for addition and subtraction operations than multiplication operation, this paper focuses on ways to decrease the number of multiplications to speed up the motion vector search. In addition to the temporal redundancy we also try to take advantage of the spatial redundancy for reducing the number of multiplications. In a simulation of motion estimation, it has proven that the proposed algorithm achieves exactly the same optimal results as the direct SSD full search, but with a processing speed of about 50 times higher.
Dynamic speckle analysis (DSA) is a non-contact method to detect movements of the inspected objects. By illuminating the observed sample using a coherent light source, motion information can be obtained from a series ...
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ISBN:
(数字)9781510646520
ISBN:
(纸本)9781510646520;9781510646513
Dynamic speckle analysis (DSA) is a non-contact method to detect movements of the inspected objects. By illuminating the observed sample using a coherent light source, motion information can be obtained from a series of reflecting speckle patterns. Conventional DSA methods record the intensity of the speckle patterns using a frame-based imaging sensor. Here, we propose a novel implementation of DSA using the event sensor which captures the brightness changes of the dynamic speckle patterns with high temporal resolution and low latency. Our method is based on the block matching algorithm in which the captured event stream is divided into many non-overlapping blocks and motion information can be computed by searching for the blocks with the highest similarity. The experimental results demonstrate the feasibility of our method in different dynamic levels, and this work will be beneficial for various applications, such as biomedical imaging and material science.
Three dimensional (3D) video is attracting a lot of attention as a new multimedia representation method. 3D video is a sequence of 3D models (frames) that consist of varying vertices and connectivity. In conventional ...
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ISBN:
(纸本)9781424404810
Three dimensional (3D) video is attracting a lot of attention as a new multimedia representation method. 3D video is a sequence of 3D models (frames) that consist of varying vertices and connectivity. In conventional 2D video compression algorithms, motion compensation (MC) using block matching algorithm is frequently employed to reduce redundancy between consecutive frames. However, there is no such technology for 3D video so far. Therefore, in this paper, we have developed an extended block matching algorithm (EMBA) to reduce temporal redundancy of geometry information of 3D video by extending the idea of 2D blockmatching to 3D space. In our EBMA, a cubic block is used as a matching unit and, MC is achieved efficiently by matching the mean normal vectors of the sub-blocks, which turned out to be sub-optimal by our experiments. The residual information is further transformed by discrete cosine transform (DCT) and then encoded. The extracted motion vectors are also entropy encoded. As a result of our experiments, compression ratio ranging from 10% to 18% of the original 3D video data has been achieved.
Motion compensation is a key operation in video compression to remove the temporal redundancy in a video sequence. One of the application examples is the MPEG video compression standard. The most commonly used motion ...
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ISBN:
(纸本)0819423564
Motion compensation is a key operation in video compression to remove the temporal redundancy in a video sequence. One of the application examples is the MPEG video compression standard. The most commonly used motion estimation algorithm is the block matching algorithm due to its regularity. Full search is the most straight forward block matching algorithm which can always locate the optimal motion vector. However, its computational complexity makes it impractical in real time applications. Fast algorithm required less computation but the obtained motion vector is suboptimal. In this paper, a hybrid block matching algorithm is proposed. In this algorithm, average intensities of groups of pixels are used to roughly estimate the motion first. Then, the fast search algorithm is applied in a reduced search region centered around the result of the first pass. Experimental results show that the performance of the estimation accuracy is quite close to that of the full search algorithm while the computational complexity is only slightly increased with respect to those fast algorithms.
In this paper, a new hysteresis modeling method based on an improved sub-pixel blocking matchingalgorithm with an optimal block size and the Preisach model is proposed to model the hysteresis behavior of a nano piezo...
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ISBN:
(纸本)9781479913343
In this paper, a new hysteresis modeling method based on an improved sub-pixel blocking matchingalgorithm with an optimal block size and the Preisach model is proposed to model the hysteresis behavior of a nano piezoelectric actuator (PA) on nano scale in a real time system. First, the Preisach model about the hysteresis behavior of a piezoelectric actuator is introduced. Then, a real time block matching algorithm is proposed and its block size is optimized with a standard object. Finally, experiments are conducted with respect to a nano-meter movement platform system, and the results show the feasibility and validity of the sub-pixel estimation based block matching algorithm and its application in modeling the hysteresis behavior of PA.
Video Error Concealment is the error hiding technique in videos. In recent years, there is huge requirement of error concealment in video applications such as in video streaming, entertainment, advertisement, media, s...
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ISBN:
(纸本)9783319636733;9783319636726
Video Error Concealment is the error hiding technique in videos. In recent years, there is huge requirement of error concealment in video applications such as in video streaming, entertainment, advertisement, media, security, etc. The simulation on MATLAB for the error videos using block matching algorithm (BMA) has been performed to achieve the concealed videos. From an error video, error frame is detected using Histogram and correlation. This frame is corrected using BMA. First step of BMA is to divide the current frame of a video into macroblock. Second step is to compare each of the macroblocks with a corresponding block and its adjacent neighbors in the frame or previous frame. Third step is to models the movement in a macroblock from one location to another. Last step is to calculate this movement for all the macro blocks that is comprising a frame. This error block is replaced by correct reference block. The quality of the error video and concealed video is measured using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index Method). An improvement in quality is observed in concealed video.
Object tracking and motion estimation are key components in large number of applications, ranging from the navigation of autonomous vehicles to video data compression. This object tracking uses the motion estimation f...
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ISBN:
(纸本)9781728146850
Object tracking and motion estimation are key components in large number of applications, ranging from the navigation of autonomous vehicles to video data compression. This object tracking uses the motion estimation for continuous tracking of distinctive features in a successive manner. This helps to detect the motion of features used in computing to detect the exact or appropriate solution by optimizing the block size. To obtain the better prediction quality by using variable size motion estimation, proposed a block matching algorithm for motion estimation, object tracking, and video data compression.
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