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P.5.250 See [E382] This paper explains clearly the fully pipelined architecture for intra prediction in HEVC and achieves a high throughput of 4 pels per clock cycle. It can decode 3840x2160 videos at 30 fps. In the conclusions the authors state “in the future work, we plan to implement the proposed architecture on ASIC platform to increase the system frequency, aiming at achieving real-time video decoding of higher resolution(higher than 4K videos)”. Explore this.

P.5.251 See P.5.250. The authors also state “Meanwhile the proposed architecture will be integrated with inter prediction engine, inverse transforming engine and other engines to construct the entire encoding/decoding system”. This is a major project. Implement this HEVC codec.

P.5.252 See [E281]. In the conclusions it is stated “Then, two flexible and HEVC compliant architectures, able to support the DCT of size 4, 8, 16, 32 have been proposed”. In beyond HEVC, DCT of size 64 also being considered. Extend these HEVC compliant architectures to support the DCT of size 64. See the sections BEYOND HEVC and PROJECTS ON BEYOND HEVC towards the end of this chapter.

P.5.253 Based on a set of Pareto-efficient encoding configurations identified through a rate-distortion-complexity analysis Correa et al [E383] have developed a scheme that accurately limits the HEVC encoding time below a predefined target for each GOP. The results also indicate negligible BD-rate loss at significant complexity reduction. Go through this paper in detail and confirm the results shown in Tables II – IV and Figs. 1 and 4-9 using the test sequences listed in Table I.

P.5.254 See [E384]. After describing the mosaic videos with arbitrary color filter arrays (Fig. 1), the authors propose a novel chroma subsampling strategy (4:2:0 format) for compressing mosaic videos in H.264/AVC and HEVC. They claim that this strategy has the best quality and bitrate compared with previous schemes.

For the seven typical RGB-CFA structures shown in Fig. 1 (captured mosaic videos) apply the demosaicking designed for each structure and as well the universal demosaicking and obtain the demosaicked full-color RGB images.

P.5. 255 See P.5.254. For the demosaicked videos convert from RGB to YUV and then to 4:2:0 six subsampling strategies (Fig.6). Convert from 4:2:0 to 4:4:4 YUV format and then to RGB reconstructed video. Compare these strategies in terms of CPSNR and CMSE for these demosaicked videos.

P.5.256 Implement the chroma subsampling strategy described in [E384] along with other strategies (Figs. 2-4) in both H.264/AVC and HEVC and confirm the results shown in Figs. 5-8 and Tables I-VI.

P.5.257 Apply the universal demosaicking algorithm based on statistical MAP estimation developed in [E387] to the seven typical RGB-CFA structures (see P.5.284) and obtain the demosaicked full color RGB images. Compare the effectiveness of this universal algorithm with those described in [E384] in terms of the PSNR. See the conclusions section in [E387].

P.5.258 See [E388]. Also the abstract. Implement the fast prediction mode decision in HEVC developed in [E388] and confirm the simulation results shown in Tables 1-3.

P.5.259 See P.5.258. Apply this technique to 8K test sequences and develop tables similar to Tables 1-3 described in [E388].

P.5.260 Review [E389] in detail. The last sentence in Conclusion section states, “The future work will focus on extending algorithm to the remaining coding structures (i.e., PUs and TUs) and other configurations in order to further expedite the encoding process with minimal impact on the coding efficiency”. Explore this and develop tables similar to Tables V-VII and draw the conclusions.

P.5.261 See [AVS12}. The authors proposed a fast intra coding platform for AVS2 (called iAVS2) leading to higher speeds and better balance between speed and compression efficiency loss especially for large size videos. The authors state “Owing to their (AVS2 and HEVC) similar frameworks, the proposed systematic solution and the fast algorithms can also be applied in HEVC intra coding design”. Go thru this paper in detail and explore how the speed up methods can be applied to intra HEVC using various test sequences based on the standard performance metrics.

P.5.262 See [E392]. SDCT and its integer approximation have been proposed and applied in image coding. The authors suggest the possibility to implement efficiently an integer SDCT in the HEVC standard.

Integrating inside HEVC may require a significant amount of work, as the transform has to be inserted in the rate-distortion optimization loop, and auxiliary information may have to be signaled. RD optimization is feasible but, the way at least the HEVC software is written, it is not necessarily easy. What can be easily done is to take the HEVC integer transform and rotate the transform using the technique developed in [E392] for obtaining a rotated transform. Implement this in all profiles and compare with the HEVC HM software. Consider both options.

P.5.263 See P.5.262 Using SDCT and its integer approximation in HEVC invariably results in increased implementation complexity. Investigate this thoroughly.

P.5.264 Performance comparison of SDCT with DCT is shown in Tables I, II and IV [E392]. However the block sizes are limited to 32x32. For super high resolution videos it is suggested that even larger block sizes such as 64x64 are suggested. Extend these Tables for 64x64 block size.

P5.265 See P.5.265. Extend these Tables to 4K and 8K video sequences.

P.5.266 Performance comparison of INTSDCT with DCT is shown in Table V [E392}. Extend this comparison to 4K and 8K video sequences and also larger block size such as 64x64.

P.5.267 In P.5.264 thru P.5.266 consider implementation complexity as another comparison metric.

P.5.268 Huang et al [E393] have developed false contour detection and removal (FCDR) method and applied it to HEVC and H.264 videos as post processing operation. They also state “It will be interesting to adopt it as part of the in loop decoding process (Fig.5.5). This idea demands further investigation and verification”. Investigate this in detail and see how FCDR can be embedded as an in loop operation besides the deblocking and SAO filters. Assuming FCDR embedding is successful, compare this with FCDR as a post processing operation in terms of PSNR, SSIM and subjective quality (See the corresponding figures and tables in [E393].) using various test sequences.

P.5.269 See P.5.268. Consider implementation complexity as another comparison metric in the FCDR process (in loop vs. post processing) in both HEVC and H.264.

P.5.270 Chen et al [394] proposed a novel block-composed background reference (BCBR) scheme and is implemented in HEVC. They claim that the new BCBR algorithm can achieve better performance than baseline HEVC. This technique is however limited to sequences captured by static cameras (surveillance and conference sequences). They also suggest, “For moving camera cases, the long-term temporal correlation due to background is also worthy of investigation and the block-composed sprite coding would be a good choice”. Investigate this in detail. Consider also encoding and decoding complexity as another performance metric.

P.5.271 See p.5.270 The authors in [394] conclude “We would like to extend our BCBR to more generic cases in our future work”. Explore this.

P.5.272 Min, Xu and Cheung [E397] proposed a fully pipeline architecture, which achieves higher throughput, smaller area and less memory, for intra prediction of HEVC. They conclude “ In the future work, we plan to implement the proposed architecture on ASIC platform to increase the system frequency, aiming at achieving real time video decoding of higher resolution.”. Implement this.

P.5.273 See P.5.272 Min, Xu and Cheung [E397] further state “Meanwhile, the proposed architecture will be integrated with inter prediction engine, inverse transforming engine, and the other engines to construct the entire full scale encoding/ decoding system.” Explore this in detail and implement the same.

P.5. 274 In [H.78] the author state “We would like to extend this sketch attack framework to handle different video coding standards such as High Efficiency Video Coding (HEVC), Audio Video Standard (AVS) and Google VP9 as our future work.” Extend this attack to HEVC Main Profile.

P.5.275 In implementing the image codec based on SDCT, Francastoro, Fosson and Magli [E392] fixed the 8 quantization levels for the angles distributed uniformly between 0 and π. They state “In order to improve the compression performance, as future work, we may consider a non-uniform angle quantization.” Investigate this thoroughly. Consider all possible non-uniform angle quantizations, the main objective being improved compression performance.
P.5.276  Wang et al [E399]  have described the MPEG internet video coding (IVC)  standard and compared its performance  (both objective and subjective    - see Figs 10-13  for   RA and  LD )  with web video coding  (WVC), video coding for browsers (VCB) and AVC high profile. They have also compared the coding tools of IVC with those of AVC HP   (Table  IV).  Using the test sequences and their configurations (Tables V-VII) confirm the results shown in Table VIII and Figs. 10-13. This project requires detailed and extensive simulations and intensive viewing by naïve and expert subjects using the double stimulus impairment scale (DSIS).

P.5.277  See P.5.276. Simulations are based on classes A, B and D test sequences  (See Table V in [E399]). Extend these simulations to classes C, E, and F test sequences  and draw the conclusions based on the IVC, WVC, VCB and AVC HP.  As in P.5.276 this project also requires detailed and extensive simulations and intensive viewing by naïve and expert subjects using the double stimulus impairment scale (DSIS).

P.5.278 In the conclusion section Wang et al [E399] state “Our team has set up an open source project xIVC, which aims to develop a real time IVC codec for HD sequences. As of now, the decoder of XIVC can decode 1080P sequences in real-time on  PC platform”.  Develop this decoder.

P.5.279. See P.5.277. Develop the real time IVC codec (encoder/decoder) for HD sequences.

P.5.280 Xu et al [E400] have developed video saliency detection using features in HEVC compressed domain and claim that their method superior to other state-of-the-art saliency detection techniques. They also state that their method is more practicable compared to uncompressed domain methods as both time and storage complexity on decoding videos can be saved. In the conclusions and future work the author’s state

There exist three directions for the future work. (1) Our work in its present form merely concentrates on the bottom up model to predict video saliency. In fact, videos usually contain some top-down cues indicating salient regions, such as human faces. Indeed, an ideal vision system, like the one of humans, requires the information flow in both directions of bottom-up and top-down. Hence, the protocol, integrating the top-down model into our bottom-up saliency detection method, shows a promising trend in future. Investigate this in detail.

P.5.281 See P.5.280. “Many advanced tracking filters (e.g., Kalman filter and particle filter) have emerged during the past few decades. It is quite an interesting future work to incorporate our method with those filters, rather than the forward smoothing filter of this paper. In that case, the performance of our method may be further improved.”. Replace the forward smoothing filter adopted in [E400] by Kalman filter and particle filter and evaluate how the performance of the video saliency detection can be further improved.

P.5.282 See P.5.280. “A simple SVM learning algorithm, the C-SVC, was developed in our work for video saliency detection. Other state-of-the-art machine learning techniques may be applied to improve the accuracy of saliency detection, and it can be seen as another promising future work”. Explore this future work.

P.5.283 See [E355]. In conclusion, the authors state “In the future more study can be made on how to facilitate software and hardware implementation.” Implement tis.
P.5.284 See P.5.283. The authors [E355] further state “We also leave it as a further study how to efficiently apply CCP to various applications including high dynamic range video coding.” Explore this for HDR video coding.

P.5.285 See [E355] Following the range extensions in HEVC (see the references at thee end), the authors have demonstrated, by using the CCP , significant coding performance improvements for both natural and screen content video.. Verify this by confirming the experimental results shown in Table I thru V and Figs. 3 and 4.

P.5.286 See [E401] Section V Conclusion is repeated here:
In conclusion, it is evident that encoder could generate decoder resource optimized video bit streams by exploiting the diversities of the decoder complexity requirements of the HEVC coding modes. In this context, the proposed complexity model for HEVC inter-frame decoding predicts the decoding complexity with an average prediction error less than 5% for both uni- and bi-predicted frames. Furthermore, the proposed encoding algorithm is capable of generating HEVC bit streams that can achieve an average decoder complexity n reduction of 28.06% and 41.19% with a BD-PSNR loss of -1.91 dB and -2.46 dB for low delay P and random access configurations, respectively, compared to the bit streams generated by the HM reference encoder. The future work will focus on extending the framework to consider both the rate and the distortion, along side the decoder’s complexity, to generate more optimized HEVC video bit streams.
Explore this future work and see how you can optimize this.

P.5.287 See [E402]. Section V Conclusion is repeated here:

In this work, an unthreaded version of the OpenHEVC decoder supporting parallel decoding at slice level is presented. Based on this decoder, implementations for several multicore chips, with and without threads support, have been tested with good results in both, performance and speedup. In the future,

parallel decoding at frame level will be integrated, which certainly will improve the speedups with more than 4 cores

Integrate the parallel decoding at the frame level and evaluate how the HEVC decoder can be speeded up.

P.5.288 A novel perceptual adaptive quantization method (AVQ) based on an adaptive perceptual CU splitting that improves the subjective quality of HEVC encoder along with less encoding time is proposed in [E403]. Confirm the simulation results shown in Table I and Figs.3 and 4.

P.5.289 See P.5.288. In Section 5 Conclusion the authors [E403] state, “In the future, we will take the both the spatial and temporal characteristics into consideration to improve coding performance further”. Explore this.

P.5.290 In Section V, the authors [E404] state, “The performance of proposed algorithm is more noticeable

at high packet error rate and low bit rate conditions. Therefore, the proposed algorithm is suitable for video transmission applications in error-prone wireless channels which have bandwidth

constraints. The perceived video quality can be improved by applying more sophisticated error concealment technique at the decoder.’ Apply error concealment techniques at the HEVC decoder and investigate how the subjective video quality can be improved.

P.5.291 Boyadjis et al [E405] have proposed a novel method for selective encryption of H.264/AVC (CABAC) and HEVC compressed bit streams. And compared with other encryption schemes (see the extensive list of references at the end). See the last para in the conclusion and future work of his paper. Explore these topics (studies).