Bagged Tree And ResNet Based Joint End-to-End Fast CTU Partition Decision Algorithm For Video Intra Coding

In the development of video coding standards, advanced ones have greatly improved the bit rate compared with those of previous generation, but also brought a huge increase in coding complexity. Coding standards, such as high efficiency video coding (HEVC), versatile video coding (VVC) and AOMedia video 2 (AV2), get the optimal encoding performance by traversing all possible combinations of coding unit (CU) partition and selecting the combination with minimum coding cost. This process of searching for the best makes up a large part of encoding complexity. To reduce the complexity of coding block partition for many video coding standards, this paper proposes an end-to-end fast algorithm for partition structure decision of coding tree unit (CTU) in intra coding. It can be extended to various coding standards with fine tuning, and is applied to the intra coding of HEVC reference software HM16.7 as an example. In the proposed method, the splitting decision of a CTU is made by a well designed bagged tree model firstly. Then, the partition problem of a 32×32 sized CU is modeled as a 17-output classification task and solved by a well trained residual network (ResNet). Jointly using bagged tree and ResNet, the proposed fast CTU partition algorithm is able to generate the partition quad-tree structure of a CTU through an end-to-end prediction process, instead of multiple decision making procedures at depth level. Besides, several effective and representative datasets are also conducted in this paper to lay the foundation of high prediction accuracy. Compared with the original HM16.7 encoder, experimental results show that the proposed algorithm can reduce the encoding time by 59.79% on average, while the BD-rate loss is as less as 2.02%, which outperforms the results of most of state-of-the-art approaches in the fast intra CU partition area.

Describing agreement in the Main Condition coding field using Canadian ICD-11 inpatient data

IntroductionCountries use varying coding standards, which impact international coded data comparability. The `main condition' (MC) field is coded within the Discharge Abstract Database as "reason for admission" or "largest resource use". ObjectiveWe offer a preliminary analysis on the frequency of and contributing factors to MC definition agreements within an inpatient Canadian dataset. MethodsSix professional coders performed a chart review between August 2016 and June 2017 on 3,000 randomly selected inpatient charts from three acute care hospitals in Calgary, Alberta. Coders classified the MC as "reason for admission", "largest resource use" or "both". Patients were admitted between 1st January and 30th June 2015 and met the inclusion criteria if they were >18 years, had an Alberta personal health care number, and had an inpatient visit for any service outside of obstetrics. Agreement between the two MC definitions was stratified by length of stay (LOS), emergency department admission, hospital of origin, discharge location, age, sex, procedures, and comorbidities. Chi-square analysis and frequency of inconsistencies were reported. ResultsOnly 34 (1.51%) of the 2,250 patient charts had disagreeing MC definitions. Age, emergency visit on admit, LOS, hospital, and discharge location were associated with MC agreement. Chronic conditions were seen more often in MC definition agreements, and acute conditions seen within those disagreeing. ConclusionThere was a small proportion of cases in which the condition bringing the patient to hospital was not also the condition occupying the largest resources. Within disagreements, further research using a larger sample size is needed to explore the presence of MC in a secondary/tertiary condition, the association between patient complexity and disagreeing MC definitions, and the nature of the conditions seen in the inconsistent MC definitions.

Improved JPEG Coding by Filtering 8 × 8 DCT Blocks

The JPEG format, consisting of a set of image compression techniques, is one of the most commonly used image coding standards for both lossy and lossless image encoding. In this format, various techniques are used to improve image transmission and storage. In the final step of lossy image coding, JPEG uses either arithmetic or Huffman entropy coding modes to further compress data processed by lossy compression. Both modes encode all the 8 × 8 DCT blocks without filtering empty ones. An end-of-block marker is coded for empty blocks, and these empty blocks cause an unnecessary increase in file size when they are stored with the rest of the data. In this paper, we propose a modified version of the JPEG entropy coding. In the proposed version, instead of storing an end-of-block code for empty blocks with the rest of the data, we store their location in a separate buffer and then compress the buffer with an efficient lossless method to achieve a higher compression ratio. The size of the additional buffer, which keeps the information of location for the empty and non-empty blocks, was considered during the calculation of bits per pixel for the test images. In image compression, peak signal-to-noise ratio versus bits per pixel has been a major measure for evaluating the coding performance. Experimental results indicate that the proposed modified algorithm achieves lower bits per pixel while retaining quality.

The SoftWipe tool and benchmark for assessing coding standards adherence of scientific software

Scientific software from all areas of scientific research is pivotal to obtaining novel insights. Yet the coding standards adherence of scientific software is rarely assessed, even though it might lead to incorrect scientific results in the worst case. Therefore, we have developed an open source tool and benchmark called , that provides a relative software coding standards adherence ranking of 48 computational tools from diverse research areas. can be used in the review process of software papers and to inform the scientific software selection process.

Evaluating the Coding Performance of 360° Image Projection Formats Using Objective Quality Metrics

Recently, 360° content has emerged as a new method for offering real-life interaction. Ultra-high resolution 360° content is mapped to the two-dimensional plane to adjust to the input of existing generic coding standards for transmission. Many formats have been proposed, and tremendous work is being done to investigate 360° videos in the Joint Video Exploration Team using projection-based coding. However, the standardization activities for quality assessment of 360° images are limited. In this study, we evaluate the coding performance of various projection formats, including recently-proposed formats adapting to the input of JPEG and JPEG 2000 content. We present an overview of the nine state-of-the-art formats considered in the evaluation. We also propose an evaluation framework for reducing the bias toward the native equi-rectangular (ERP) format. We consider the downsampled ERP image as the ground truth image. Firstly, format conversions are applied to the ERP image. Secondly, each converted image is subjected to the JPEG and JPEG 2000 image coding standards, then decoded and converted back to the downsampled ERP to find the coding gain of each format. The quality metrics designed for 360° content and conventional 2D metrics have been used for both end-to-end distortion measurement and codec level, in two subsampling modes, i.e., YUV (4:2:0 and 4:4:4). Our evaluation results prove that the hybrid equi-angular format and equatorial cylindrical format achieve better coding performance among the compared formats. Our work presents evidence to find the coding gain of these formats over ERP, which is useful for identifying the best image format for a future standard.