A Modified 2-D Logarithmic Search Technique for Video Coding

A Modified 2-D Logarithmic seek Technique for Video Coding With Reduced essay Points Tahmina Akhtar, Rahima Akter, Chhalma Sultana Chhaya , Ashfaqur Rahman Military Institute of Science and technology/Dept of CSE, Dhaka, Bangladesh, Central Queensland University/Centre for Intelligent and Nedeucerked Systems, QLD, Australia emailprotected com, emailprotected com, emailprotected com, a. emailprotected edu. au Abstract Video cryptanalytics is a process for repre moveing picture sequences in a compact manner.A significant bill in picture show coding is anticipateing for similar segments in previous builds and use only the difference information for reconstruction frankincense reducing piazza requirement. Different inquisition proficiencys including abounding take care and 2-D logarithmic reckon etc. are used in the current literature. in full look to restricts its application because of its computational load. 2D logarithmic hunt is computationally less expensive alth ough there are few spaces for improvement. In this paper we propose a new face proficiency by modifying the 2-D logarithmic search that requires less search promontorys with insignificant loss in visual quality.Experimental results demonstrate the efficientness of the proposed technique. Keywords video coding, 2-D logarithmic search. i. basis Video is a sequence of still images representing scenes in motion. A video is created by capturing a numbers of still images in a short snip interval. When these still images are displayed very quickly, it represents the motion of the object in the images. Video represent the huge occur of info. In order to transfer video data from one place to another efficiently it is required to compress the size of video data.One way to compress the size of video data is video coding 1 2 . The principal goal in the design of a video-coding system is to reduce the transmittance rate subject to some picture quality constraint. In transmission sid e, the for the first time frame (normally called the reference frame) is transmitted as it is and the remaining frames are sent as a function of the reference frame. The frame to be sent is divided into a number of put offs and the best match for the block is looked for in the search window of the reference frame. This processing is called the search technique in video coding literature.There exist a number of video coding techniques including MPEG-1/2/4 2 7 , H. 26X 8 etc. uses search techniques like Full search 1 , 2-D logarithmic search 3 , Coarse-Fine-Three-Step search 4 , Conjugate Direction search 5 , and Pyramid search 6 . Each of these search techniques has merits and demerits in their favor. Full search finds the best match for a block as it searches all the candidate positions in the search window. Full search however is computationally expensive and renders difficulty for real time implementation.Some variants exist that applies some heuristics to reduce the c andidate search points and reduce the computational complexity although compromising the image quality a bit. 2-D logarithmic search is one such search technique that reduces the search points to a subset of the search window (to be detailed in literature review) and finds the near-optimal best match with reduced computational complexity. Although computationally chinchy it contains some redundancy in the search space. We aim to reduce this redundancy and aim to find a modified 2-D logarithmic search technique with fifty-fifty reduced computational load.Experimental results demonstrate that the proposed technique reduces the number of search points and thus reduces search time with insignificant sacrifice of image quality. The paper is organized as fol petty(a)s. In Section II we elaborate some related works. In Section III we present our proposed search approach. Some experimental results to demonstrate the effective of the proposed approach is presented in Section IV. Finally Se ction V concludes the paper. II. Related works In this section we present full search technique and the logarithmic search technique.In both cases the frame to be coded is divided into a number of non-oerlapping equal size blocks of size p? q. The best match is looked for in a search window of size (2d+1)? (2d+1) in the reference frame . figure 1 Block matching process in video coding that uses search techniques. * A. Full Search In Full search 1 finds the best match by inspecting all the (2d+1)? (2d+1) candidate positions within the search window. Full search cognitive process is brute force in nature. The advantage of Full Search is that it delivers good accuracy in searching for the best match.The disadvantage is that it involves a large amount of computation. * B. 2-D Logarithmic Search Jain and Jain 3 developed a 2-D logarithmic search technique that successively reduces the search area, thus reducing the computational burden. The first step computes the similarity for fi ve points in the search window. These five points are as follows the central point of the search window and the four points surrounding it, with individually being a midpoint between the central point and one of the four boundaries of the window. Among these five points, the one corresponding to the minimum dissimilarity is picked as the winner.In the attached step, surrounding this winner, another set of five points are selected in a similar fashion to that in the first step, with the distances between the five points remaining unchanged. The ejection takes place when either a central point of a set of five points or a boundary point of the search window gives a minimum dissimilarity. In these circumstances, the distances between the five points need to be reduced. The procedure continues until the final step, in which a set of candidate points are located in a 33 2-D grid.The steps in a 2-D logarithmic search technique are presented in design 2. Fig 2 The 2-D logarithmic searc h technique. The circle numbered n is searched at the n-th step. The arrows indicate the points selected as the center of the search for the abutting guide on. The 2-D logarithmic search hits a maximum of 18 points and a minimum of 13 search points. The advantage of this technique is that it successively reduces the search area, thus reducing the computational burden. One of the disadvantages is that some points are searched more than erstwhile thus leave some space for improvement.Moreover, it follows a greedy approach by selecting the minimum dissimilar point at each step thus posing a threat to follow a local minimum trend. Considering these facts we propose to modify the 2-D logarithmic search to overcome the local minimum difficulty and also eliminate the redundant computing as described in the following section. iii. proposed search technique We mainly modified the 2-D logarithmic search technique to eliminate the redundancy and local minimum problem associated with it. Th e search technique is elaborated next under the light of 2-D logarithmic search technique.Our proposed search technique starts with the five points in the search window where the one is at the center and other four surrounds center point (Fig 3(a)). Unlike 2-D logarithmic search, our proposed technique selects two points min1 and min2 (Fig 3(b)) that has dissimilarity scores lower than the other three points. We then select a point as the center of search for the next pass that lies on the line in between min1 and min2. This selection reduces the local minimum effect as it simply does not follow the minimum point.Moreover, the five points selected in the next pass does not match with any of the previous points thus eliminates the redundancy that exists in 2-D logarithmic search. Centered at the point selected at the next pass the search continues (Fig 3(d)-Fig 3(f)). The steps of the search are portrayed in Fig 3. Following are some of the merits of our proposed technique * Successi vely reduces the search area with no point searched twice * Maximum search points are 12 and minimum search points are 5 an improvement over 2-D logarithmic search. iv. Results and DiscussionWe have conducted a comparative analysis of Full Search, 2-D logarithmic Search and our proposed search technique as presented next. All the experiments were conducted on MPEG sequences using MATLAB. We used sequences like garden, Akiyo, Table Tennis, automobile, and coastguard. Full search, 2-D logarithmic search and our proposed technique applied in these standard MPEG file and we computed the ASNR (Average Signal to Noise Ratio) and Computational load (i. e. number of search points). The results on diametric sequences are presented next. Akiyo Sequence Each frame of the Akiyo sequence is of 352? 88 pixels, record at 25 frames per arcsecond and there are a total of 398 video frames. Fig 4 shows the reconstructed 20th frame of Akiyo sequence coded using Full search, 2D-logarithmic search an d proposed search technique. In this video only face region is moving. Search point comparison for these three search techniques is presented in Fig 5 and ASNR is reported in Fig 6. ASNR achieved using the proposed search technique is near equal 2D logarithmic search but at reduced number of search points (Fig 5). Number of search points remains some similar over the different frames.ASNR value shown in Table 1. (a) (b) (c) (d) (e) (f) Fig 3 The different steps of our proposed 2-D logarithmic search technique. (a) five points of search window, (b) the direction of the search in between the direction offered by the two points min1 and min2. (c) Search at step 2, (d) min1 and min2 at step 2, (e) Search points at step 3, and (f) Search ends at the patrician point. (a) (b) (c) Fig 4 retrace 20th frame of the Akiyo sequence using (a) Full search, (b) 2-D logarithmic search, and (c) Our proposed search technique.Fig 5 similitude of of search points for Akiyo sequence. Fig 6 Compari son of ASNR for Akiyo sequence. Table 1 ASNR value of different search for Akiyo sequence Frame No Full Search 2D logarithmic Search Proposed Search first 25. 86188 25. 55678 25. 46245375 5th 24. 84504 23. 77938883 23. 57562323 10th 24. 37532 23. 01043038 22. 67351877 15th 24. 38495 22. 98908004 22. 5831958 20th 24. 4424 22. 90227928 22. 56886825 twenty-fifth 24. 44956 23. 03416597 22. 51615637 Car Sequence Each frame of the Car sequence is of 320? 240 pixels and ecorded at 25 frames per second and there are a total of 398 video frames. The reconstructed 20th frame of Car sequence using the three search techniques is presented in Fig 7. In this video sequence the car moves but background is still. Here each repeated two times. Average no of search point is more or less 10. 46 for repeated frames and 11. 50 for new frames. Here number of search points vary significantly compared to Akiyo sequence. boilersuit the proposed technique has reduced search points (Fig 8) although the ASNR is bit low (Fig 9). ASNR value of some frames shown in Table 2. a) (b) (c) Fig 7 Reconstructed 20th frame of the Car sequence using (a) Full search, (b) 2-D logarithmic search, and (c) Our proposed search technique. Fig 8 Comparison of of search points for Car sequence. Fig 9 Comparison of ASNR for Car sequence. Table 2 ASNR value of different search for Car sequence Frame No Full Search 2D logarithmic Search Proposed Search 1st 27. 13312 26. 5682 26. 08265 5th 26. 68718 25. 75123 25. 16904 10th 26. 10589 25. 12647 24. 27394 15th 26. 31185 25. 16266 24. 54981 20th 26. 28613 25. 1915 24. 61234 25th 25. 86261 25. 02255 24. 12599 Garden Sequence Each frame of the Garden sequence is of 352? 240 pixels and recorded at 30 frames per second and there are a total of 59 video frames. Fig 10 represents the reconstructed 20th frame of this sequence coded using the three search techniques. In this video the motion is due to photographic camera movement. Fig 11 and Fig 12 reveals that the new search technique reduces the number of search points with minor loss in ASNR. ASNR value of some frames shown in Table 3. Here Average no of search point for each frames required almost same.In frame 20th average no of search point is 11. 6053 and ASNR is 18. 22931. (a) (b) (c) Fig 10 Reconstructed 20th frame of the Garden sequence using (a) Full search, (b) 2-D logarithmic search, and (c) Our proposed search technique. Fig 11 Comparison of of search points for Garden sequence. Fig 12 Comparison of ASNR for Garden sequence. Table 3 ASNR value of different search for Garden sequence Frame No Full Search 2Dlogarithmic Search Proposed Search 1st 24. 27663 24. 27663 23. 5971 5th 21. 6078 21. 6078 20. 49847 0th 20. 71779 20. 71779 19. 34323 15th 19. 9641 19. 9641 18. 69269 20th 19. 6754 19. 6754 18. 22931 25th 19. 39791 19. 39791 18. 05226 Coastguard Sequence Each frame of the Coastguard sequence is of 320? 240 pixels and recorded at 25 frames per second and there are a total of 378 vi deo frames. Here the boat and the camera are moving. Fig 13 represents a reconstructed frame of this sequence coded using the three search techniques. Fig 14 represents the search point required by the three techniques. Our proposed technique shows periodic nature in terms of search points.This is due to the repetitive nature of motion in the video. Fig 15 represents a comparison of ASNR obtained using different techniques. Table 4 shown ASNR of some frames. (a) (b) (c) Fig 13 Reconstructed frame of the Coastguard sequence using (a) Full search, (b) 2-D logarithmic search, and (c) Our proposed search technique. Fig 14 Comparison of of search points for Coastguard seq. Fig 15 Comparison of ASNR for Coastguard sequence. Table 4 ASNR value of different search for Coastguard seq. Frame No Full Search 2D logarithmic Search Proposed Search 1st 24. 8771 24. 33338 23. 61801 5th 24. 31753 23. 35416 22. 54516 10th 23. 90367 23. 03317 22. 07546 15th 24. 36529 23. 44171 22. 66604 20th 24. 3865 8 23. 26823 22. 50994 25th 24. 54524 23. 91583 22. 91885 Table tennis Sequence Each frame of the Table tennis sequence is of 352? 240 pixels and recorded at 30 frames per second and there are a total of 9 video frames. Here ball is moving fast. The reconstructed frames, number of search points, and ASNR of the three search techniques are presented in Fie 16, Fig 17, and Fig 18. Some ASNR of Table tennis sequence shown in table 5. a) (b) (c) Fig 16 Reconstructed frame of the Table tennis sequence using (a) Full search, (b) 2-D logarithmic search, and (c) Our proposed search technique. Fig 17 Comparison of of search points for Table tennis sequence. Overall the result of ASNR for Full Search is best in all cases but number of search point is so high. The result of ASNR for 2-D logarithmic and our proposed search is almost same but the number of search point of our proposed search is smaller than the 2-D logarithmic search and thus an improvement over the existing technique.Fig 18 Com parison of ASNR for Table tennis sequence. Table 5 ASNR value of different search for Table tennis seq Frame No Full Search 2D logarithmicSearch ProposedSearch 1st 25. 2698 24. 56416 23. 90544 3rd 23. 60795 22. 69326 21. 81273 5th 23. 43996 22. 35007 21. 29301 7th 23. 71878 22. 71607 21. 58383 v. Conclusion In this paper we have presented a new search technique for video coding that is a modification of the existing 2-D logarithmic search. The proposed technique reduces the search time of 2-D logarithmic search by reducing the redundant search points.Although ASNR is sacrificed to some extent it had insignificant visual impact as observed from the experimental results. References 1 Shi and H. Sun, Image and Video Compression for Multimedia technology, Fundamentals, Algorithms and Standards, 2nd Edition. 2 P. N. Tudor, MPEG-2 Video Compression, IEEE J Langham Thomson Prize, Electronics and Communication Engineering journal, December 1995. 3 J. R. Jain and A. K. Jain, Displacement Me asurement and Its Application in Interframe Image Coding, IEEE Transactions on Communications, vol. com-29, no. 12, December 1981. 4 T. Koga, K. Linuma, A. Hirano, Y. Iijima, and T.Ishiguro, Motion-compensated interframe coding for video conferencing, Proc. 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