High Efficiency Video Coding (HEVC) adopts the quadtree structured coding unit (CU), which allows recursive splitting into four equally sized blocks. At each depth level, it enables SKIP mode, Merge mode, Inter 2N×2N, Inter 2N×N, Inter N×2N, Inter 2N×nU, Inter 2N×nD, Inter nL×2N, Inter nR×2N, Inter N×N (only available for the smallest CU), Intra 2N×2N and Intra N×N (only available for the smallest CU) in inter frames. Similar to H.264/AVC, the mode decision process in HEVC is performed using all the possible depth levels (or CU sizes) and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency, but leads to a very high computational complexity. Since the optimal prediction mode is highly content-dependent, it is not efficient to use all the modes. In this paper, we propose a fast inter mode decision algorithm for HEVC by jointly utilizing the inter-level correlation of quadtree structure and the spatio-temporal correlation. There exist strong correlations of the prediction mode, the motion vector and RD cost between different depth levels and between spatially-temporally adjacent CUs. We statistically analyze the prediction mode distribution at each depth level and the coding information correlation among adjacent CUs. Based on the analysis results, three adaptive inter-mode decision strategies are proposed including early SKIP mode decision, prediction size correlation based mode decision and RD cost correlation based mode decision. Experimental results show that the proposed overall algorithm can save 49%-52% computational complexity on average with negligible loss of coding efficiency, exhibiting applicability to various types of video sequences.

Adaptive Inter-Mode Decision for HEVC Jointly Utilizing Inter-Level and Spatiotemporal Correlations

Scalable video coding is an ongoing standard, and the current working draft (WD) is an extension of H.264/AVC. In the WD, an exhaustive search technique is employed to select the best coding mode for each macroblock. This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. This paper proposes a fast mode decision algorithm for inter-frame coding for spatial, coarse grain signal-to-noise ratio, and temporal scalability. It makes use of the mode-distribution correlation between the base layer and enhancement layers. Specifically, after the exhaustive search technique is performed at the base layer, the candidate modes for enhancement layers can be reduced to a small number based on the correlation. Experimental results show that the fast mode decision scheme reduces the computational complexity significantly with negligible coding loss and bit-rate increases

Fast Mode Decision Algorithm for Inter-Frame Coding in Fully Scalable Video Coding

The H.264 video coding standard significantly outperforms previous standards in terms of coding efficiency. However, this comes as a cost of extremely high computational complexity due to mode decision where variable block size motion estimation (ME) is employed. In this paper, we propose an efficient algorithm to jointly optimize mode decision and ME. A theoretical analysis is performed to study the sufficient condition to detect all-zero blocks in H.264, and thus adaptive thresholds are derived to early terminate mode decision and ME. Besides the aforementioned early termination technique, the proposed algorithm also introduces temporal-spatial checking, thresholds based prediction and monotonic error surface based prediction methods to skip checking unnecessary modes. Experimental results demonstrate that the proposed algorithm can significantly reduce the computational complexity of H.264 encoding while maintaining almost the same rate distortion (RD) performance as the original encoder

An Efficient Mode Decision Algorithm for H.264/AVC Encoding Optimization

The H.264 video coding standard significantly outperforms previous standards in terms of coding efficiency. However, this comes as a cost of extremely high computational complexity due to mode decision where variable block size Motion Estimation (ME) is employed. In this paper, we propose an efficient algorithm to jointly optimize mode deci- sion and ME. A theoretical analysis is performed to study the sufficient condition to detect all-zero blocks in H.264, and thus adaptive thresholds are derived to early terminate mode decision and ME. Besides the afore- mentioned early termination technique, the proposed algorithm also intro- duces temporal-spatial checking, thresholds based prediction and mono- tonic error surface based prediction methods to skip checking unnecessary modes. Experimental results demonstrate that the proposed algorithm can significantly reduce the computational complexity of H.264 encoding while maintaining almost the same Rate Distortion (RD) performance as the orig- inal encoder. Index Terms—Early termination, H.264, integer DCT, mode decision, motion estimation.

An Efficient Mode Decision Algorithm for H.264/AVC

Multi-view video coding (MVC) is an ongoing standard in which variable size disparity estimation (DE) and motion estimation (ME) are both employed to select the best coding mode for each macroblock (MB). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. In this paper, a fast DE and ME algorithm based on motion homogeneity is proposed to reduce MVC computational complexity. The basic idea of the method is to utilize the spatial property of motion field in prediction where DE and variable size ME are needed, and only in these regions DE and variable size ME are enabled. The motion field is generated by the corresponding motion vectors (MVs) in spatial window. Simulation results show that the proposed algorithm can save 63% average computational complexity, with negligible loss of coding efficiency.

Selective Disparity Estimation and Variable Size Motion Estimation Based on Motion Homogeneity for Multi-View Coding

The new video coding standard, H.264/MPEG-4 AVC, uses variable block sizes ranging from 4/spl times/4 to 16/spl times/16 in interframe coding. This new feature has achieved significant coding gain compared to coding a macroblock (MB) using fixed block size. However, this feature results in extremely high computational complexity when brute force rate distortion optimization (RDO) algorithm is used. This paper proposes a fast intermode decision algorithm to decide the best mode in intercoding. It makes use of the spatial homogeneity and the temporal stationarity characteristics of video objects. Specifically, spatial homogeneity of a MB is decided based on the MB's edge intensity, and temporal stationarity is decided by the difference of the current MB and it colocated counterpart in the reference frame. Based on the homogeneity and stationarity of the video objects, only a small number of intermodes are selected in the RDO process. The experimental results show that the fast intermode decision algorithm is able to reduce on the average 30% encoding time, with a negligible peak signal-to-noise ratio loss of 0.03 dB or, equivalently, a bit rate increment of 0.6%.

Fast intermode decision in H.264/AVC video coding

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

D. Wu

Author Tools

Chat about Author

Papers

Fast intermode decision in H.264/AVC video coding