Jain, J. and Jain, A. (1981). Displacement measurement and its application in interframe image coding. IEEE Trans. Commun., COM-29:1799--1808.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....a cumulative histogram in the pose space presents two main problems which are the size of the pose space ( H R ) and the presence of false peaks. Therefore, we have considered a recursive search algorithm. The method is inspired from an algorithm proposed for a fast block matching algorithm [11]. First, #T is minimized using large variation steps of the parameters. When the current minimum is found, the process is iterated with smaller variation steps around this value. In practice, the initial solution is a proper initialization of this search algorithm. Therefore, we ....

J. Jain and A. Jain. Displacement measurement and its application in interframe image coding. IEEE Trans. on Communications, 29(12):1799--1808, December 1981.

....range, but instead use a heuristic approach to guide the search. These methods examine only a subset of the possible locations within the search range, and hence can be computed very efficiently. Some of the most popular methods are the three step search [8] the two dimensional logarithmic search [6], and their many successful variants such as the one found in [3] Because of their speed, these suboptimal methods are of great interest. However, they are prone to getting trapped in local minima and thus are not appropriate for applications which require a maximum PSNR. The second category, ....

J. R. Jain and A. K. Jain. "Displacement measurement and its application in interframe image coding," IEEE Transactions on Communications, COM-29(12):1799-1808, 1981.

....two men walking, revolving door, and close up of a document. predicted and backward predicted, and two for bi directionally interpolated. The MPEG standard does not specify how such vectors are to be computed, however. Because of the block based motion representation, block matching techniques [JJ81, GM90, LZ93] are usually used. In a block matching technique, the motion vector is obtained by minimising a cost function measuring the mismatch between a block and its predicted candidate block. Let M i be a macroblock in the current picture P c , and v the displacement with respect to the ....

....the objects compared with its focal length. Here the term panning is used to refer to both panning and tilting as the only di#erence between them is the rotation direction. Motion vectors can be obtained by optical flow computation techniques [HS81, Nag87] or by coding algorithms such as MPEG [JJ81, AN88, GM90, LZ93] Although motion vectors in an MPEG stream do not represent the true optical flow, they are a good approximation in video sequences that do not contain large uniform regions. As a result, motion vectors from an MPEG stream are used here for panning and zooming detection. Paper ....

J.R. Jain and A.K. Jain. Displacement measurement and its application in interframe image coding. IEEE Transactions on Communication, 29:1799--1808, 1981.

....is an interesting one, because a limited search area reduces the possibility of finding a best match and an exceedingly large search area results in many unnecessary computations. In order to reduce the number of computations, many search area traversing methods have been proposed in literature [11, 7, 9, 8]. The second issue relates to finding a metric that will guarantee a good coding performance. Two of such metrics are the mean square error (MSE) and the mean absolute difference (MAD) Considering that block based motion estimation is most commonly used in multimedia standards such as MPEG1 ....

J. R. Jain and A. K. Jain. Displacement Measurement and Its Applications in Interframe Image Coding. IEEE Transactions on Communications, COM29 (12):1799--1808, December 1981.

....size motion estimation. I. Introduction The motion compensated transform coding technique, which exploits the temporal redundancies in the moving images via motion estimation, is one of the most popular techniques currently used in image sequence coding. The block matching algorithms (BMA s) [2] are commonly used to estimate the motion vectors because of their relative simplicity in hardware realization. However, since the boundaries of moving objects do not normally coincide with the boundaries of the BMA blocks, the objects undergoing different types of motion exist within the block. ....

....the efficient selection for the VBS motion, based on the R D constraint, was introduced. Extensive computer simulation employing the motion compensated transform coding technique showed that an overall improvement of up to 1. 0 dB was obtainable, compared to the fixed block size motion estimation [2]. ....

J. R. Jain and A. K. Jain, "Displacement measurement and its application in interframe image coding," IEEE Trans. Commun.,vol. COM-29, pp. 1799--1808, Dec. 1981.

....can then be stopped whenever a good enough match has been found. Most of these ME FS techniques are suboptimal, i.e. they do not find the best match within the search region, although the degradation as compared to exhaustive search tends to be small. Examples of fast search for ME include [1], 2] 3] 4] and [5] In the VQ case, there are many FS algorithms that achieve the optimal solution ( 6] 7] 8] 9] 10] In these approaches codewords that are known to be too far from the input are eliminated first, then the exhaustive search is performed on the rest of the codewords. ....

....spent in our software simulation on the PentiumII 300 MHz. Both distortion and complexity units are normalized by the results of DTFM. We traverse along complexity distortion curve by increasing P f from 0.01 to 0.2. In Figure 2, we show our HTFM applied to exhaustive search, 2 D Log search [1] and ST1 search [5] 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1 1.01 1.02 1.03 1.04 1.05 1.06 1.07 Mobile complexity vs. residue energy HTFM2 adaptive normalized residue energy normalized complexity (pixel comparisons clock) ST1 search : Log search Full search 1 1.05 1.1 ....

J. Jain and A. Jain, "Displacement measurement and its application in interframe image coding," IEEE Trans. on Comm., 1981.

....the metric will be computed, i.e. fast search (FS) or reducing the complexity of the metric calculation itself, i.e. fast matching (FM) In the FS approach, only a subset of promising candidates in the search region, in (2) is considered. Examples of FS approaches include the 2 D log search [1], the new three step search [2] and the diamond center based search [3] These algorithms are based on the monotonicity assumption of the matching metric as a candidate vector moves further away from the global minimum. A good initial point can also be used to reduce the risk of being trapped in ....

J.R. Jain and A.K. Jain, "Displacement measurement and its application in interframe image coding," IEEE Trans. on Comm., vol. COM-29, pp. 1799--1808, December 1981.

.... best motion vector mv = mv x ; mv y ; mv t = 1) where mv x and mv y are the spatial displacements, and mv t is the temporal displacement, is searched using a conventional single frame motion search algorithm (e.g. full search (FS) three step search [4] or two dimensional logarithmic search [5]) in the most recent reference frame located in a frame bu er. The directed search strategy uses the best match in frame f t 1 as well as the results of matching blocks in frame f t 1 to blocks in frame f t 2 . The best match for frame f t 1 overlaps up to 4 macro blocks for which motion was ....

....search strategy. Directed Search I Directed Search II T [sec] PSNR [dB] T [sec] PSNR [dB] Foreman(QCIF) 6.49 29.81 6.47 29.81 Stefan(QCIF) 9.47 22.07 9.42 22.06 Mother daughter(QCIF) 6.24 34.70 6. 24 34.70 (e.g. full search (FS) three step search [4] or two dimensional logarithmic search [5]) in the most recent reference frame located in a frame bu er, and the results are stored. The directed search strategy uses the best match in frame f t 0 1 as well as the results of matching macro blocks in frame f t 0 1 to blocks in frame f t 0 2 . B t 0 1 (i; t 0 ) overlaps up to 4 ....

J. Jain and A. Jain, \Displacement Measurement and its Application in Interframe Image Coding," IEEE Trans. on Comm., vol. 29, no. 12, pp. 1799-1808, Dec. 1981.

....algorithms have been developed [15] 16] to reduce the computational cost. They can be categorized into different groups as detailed below. 3.1 Review on the Other Fast Algorithms 3.1. 1 Fast Block Matching with Unimodal Error Surface As sumption Most fast block matching algorithms [18] [22] restrict the number of search locations using the unimodal error surface assumption, namely, the matching error in creases monotonically as the search moves away from the position of the global minimum error. However, this assumption usually does not hold, and as a result, the search could be ....

....block independently and tend to result in a noisy motion field and create the blocking effect in reconstructed images. Some well known algorithms in this class are the three step search ( TSS ) 21] four step search [19] cross search algorithm [18] and the two dimensional logarithmic search [22]. 3.1.2 Fast Block Matching with Pixel Subsampling Another interesting technique to reduce the complexity of MV estimation is block matching with pixel subsampling [24] 25] Instead of limiting the number of search locations, the number of pixels used in matching error computation is reduced. ....

J. R. Jain and A. K. Jain, "Displacement measurement and its application in inter- frame image coding," IEEE Trans. on Communications, pp. 1799 - 1808, December 1981.

....video sequence with a lower data rate will have a poorer visual quality after being decompressed. Among these three factors, the computation complexity directly a#ects the time needed to compress a video sequence. For example, the MPEG standard uses block based motion compensated prediction [10, 11, 12]. The MPEG encoding algorithms have to search for the motion vectors, which is a computationally intensive task. For example, if the sequence has a resolution of 720x480 pixels per frame (ITU R 601) the search space is a 15 15 pixel array, and the motion vector search is performed on 20 frames ....

....a 15 15 pixel array, and the motion vector search is performed on 20 frames (P frames and B frames) every 4second, the processor must be able to handle 720 480 15 15 20 # 1. 55 10 9 pixels per second for the motion vector search [13, 14] Although many fast algorithms have been proposed [10, 15, 16], the amount of computation is still overwhelming. Thus the MPEG algorithm is notoriously asymmetric, i.e. the amount of computation required for the encoding algorithm is much larger than that required for the decoding algorithm. Thus, real time video compression is di#cult to achieve and is very ....

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J. R. Jain and A. K. Jain, "Displacement measurement and its application in interframe image coding," IEEE Transactions on Communications, vol. COM29, no. 12, pp. 1799--1808, December 1981.

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Jain, J. and Jain, A. (1981). Displacement measurement and its application in interframe image coding. IEEE Trans. Commun., COM-29:1799--1808.

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J.R.Jain and A.K.Jain, "Displacement measurement and its application in interframe image coding", IEEE Trans. Commun., vol. COM-29, pp. 1799-1808, Dec. 1981

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J. R. Jain, A. K. Jain, Displacement measurement and its application in interframe image coding, IEEE Trans. Commun. 29 (12) (1981) 1799--1808.

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J.R.Jain and A.K.Jain, "Displacement measurement and its application in interframe image coding", IEEE Trans. Commun., vol. COM-29, pp. 1799-1808, Dec. 1981

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Jaswant R. Jain and Anil K. Jain, "Displacement Measurement and Its Applications in Interframe Image Coding," IEEE Transactions on Communications, vol. COM-29, no. 12, pp. 1799--1808, December 1981.

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J. R. Jain and A. K. Jain. Displacement Measurement and Its Applications in Interframe Image Coding. IEEE Transactions on Communications, COM29 (12):1799--1808, December 1981.

No context found.

J. Jain and A. Jain. Displacement measurement and its application in interframe image coding. IEEE Trans. on Communications, 29(12):1799--1808, December 1981.

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Jain, J.R. and Jain, A.K., Displacement Measurement and Its Application in Interframe Image Coding, IEEE Trans. on Communications,vol.COM-

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J.R.Jain and A.K.Jain. "Displacement measurement and its application in interframe image coding," IEEE Trans. Communications., vol. COM-29, pp 1799-1808, Dec. 1981.

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J. R. Jain and A. K. Jain, "Displacement measurement and its application in interframe image coding," IEEE Trans. Communications, vol. 29, no. 12, Dec. 1981, 1799-1808.

No context found.

J. R. Jain and A. K. Jain. Displacement Measurement and Its Applications in Interframe Image Coding. IEEE Transactions on Communications, COM-29(12):1799--1808, December 1981.

No context found.

J. R. Jain and A. K. Jain, \Displacement measurement and its application in interframe image coding," IEEE Trans. Commun.,vol. COM-29, pp. 1799-1808, Dec. 1981.

No context found.

J. R. Jain and A. K. Jain. Displacement Measurement and Its Applications in Interframe Image Coding. IEEE Transactions on Communications, COM-29(12):1799--1808, December 1981.

No context found.

J. R. Jain and A. K. Jain. "Displacement measurement and its application in interframe image coding " IEEE Trans. on Communications. Vol. com-29, No. 12, pp. 1799-1808, 1981.

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J. R. Jain and A. K. Jain. "Displacement measurement and its application in interframe image coding " IEEE Trans. on Communications. Vol. 29, No. 12, pp. 1799-1808, 1981.

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