Andreas Heindel

Open source HEVC analyzer for rapid prototyping (HARP)

The design of new HEVC extensions comes with the need for careful analysis of internal HEVC codec decisions. Several bitstream analyzers have evolved for this purpose and provide a visualization of encoder decisions as seen from a decoder viewpoint. None of the existing solutions is able to provide actual insight into the encoder and its RDO decision process. With one exception, all solutions are closed source and make adaption of their code to specific implementation needs impossible. Overall, development with the HM code base remains a time-consuming task. Here, we present the HEVC Analyzer for Rapid Prototyping (HARP), which directly addresses the above issues and is freely available under www.lms.lnt.de/HARP.

Fast intra mode decision in HEVC using early distortion estimation

The latest video coding standard HEVC has the potential to rapidly conquer many areas of video compression due to the significant boost in coding efficiency compared to its predecessor. Unfortunately there is the drawback that this gain in efficiency comes at the expense of complexity. Encoders have to select the best possible coding mode from a huge set of available modes offered by the standard. In this paper the intra mode selection process is accelerated by early estimation of the distortion introduced by a certain mode, which may be applied in addition to other fast mode decision schemes. Due to the online adaptation of our proposed estimator, the approach is tolerant to different coding settings and input sequences. Using early distortion estimation results in a potential encoder speed-up of 24.83% on average, accompanied by an average bitrate increase of 2.92%.

Fast CU split decisions for HEVC inter coding using support vector machines

High Efficiency Video Coding (HEVC) is known to be the state of the art in video compression. However, aiming at real-time applications, its very high number of possible coding options makes it necessary to approximate the selection of coding modes by fast algorithms. For this purpose Coding Unit (CU) split decisions are made by Support Vector Machine (SVM) classifiers in this paper. We use one SVM model per depth and the traditional Rate-Distortion Optimization (RDO) is used as fallback method in the case of uncertain SVM decisions. Regarding the sequence classes ClassB to ClassE, the proposed algorithm achieves encoding time reductions of more than 60%, accompanied by only 1.8% additional bitrate (lowdelay main configuration). Considering all sequence classes from ClassA to ClassF, the additional bitrate increases to 4% for the lowdelay main and about 3% for the randomaccess main configuration, with a similar encoding time reduction of more than 60%.

Fast exclusion of angular intra prediction modes in HEVC using reference sample variance

Intra picture coding using HEVC is very efficient and is applied to video as well as single image compression. However, the cost for this high compression efficiency is the complexity caused by the high number of 35 available coding modes. Existing methods for fast mode decision estimate the mode costs based on the prediction error samples. This paper proposes a smart method to exclude the 33 angular prediction modes of HEVC even before prediction, if they are unlikely to deliver a small prediction error. The sensitivity of excluding these modes can be adjusted by a threshold. Completely disregarding the angular modes leads to a very high bitrate increase compared to the unmodified encoder of almost 18% with a time saving of 51%. However, excluding the modes using an exemplary threshold value, the encoding time can be reduced by more than 20%, accompanied by a bitrate increase of only 0.7%.

Two-stage exclusion of angular intra prediction modes for fast mode decision in HEVC

The latest video compression standard HEVC sets new benchmarks concerning the efficiency for both video coding and also still image coding, i.e., pure intra picture coding. Nevertheless, its high complexity created by the rate-distortion optimization procedure is a serious drawback. To reduce this computational burden, several algorithms for fast mode decision have been proposed. However, most of these methods exclude modes based on analyzing the respective prediction errors. In this paper we present an algorithm for individual angular prediction mode exclusion which intervenes earlier, namely before prediction, almost solely based on the analysis of the reference samples. It is proposed to use this approach as an extension of the global angular intra mode exclusion scheme based on the reference samples from our previous work. The combined algorithm achieves average encoding time savings of approximately 25%, accompanied by only about 1.0% bit rate increase.

Low-Complexity Enhancement Layer Compression for Scalable Lossless Video Coding Based on HEVC

Lossless compression is desired, especially for professional applications like medical imaging. However, scalability may be necessary to transmit a fast preview of pictures when the channel capacity is limited. Furthermore, there may be the need for random access to single frames of a losslessly reconstructed video. We present and evaluate a lossy-to-lossless scalable video coding system in which the scalability is achieved by using a lossy base layer (BL) in conjunction with lossless compression of the reconstruction error in the enhancement layer (EL). High Efficiency Video Coding (HEVC) is employed for encoding the BL. For compression of the EL, we propose a low-complexity scheme called sample-based weighted prediction for EL coding (SELC). Furthermore, EL compression using JPEG-LS and the scalable extension of HEVC (SHVC) are evaluated. The performance of scalable coding using each of these three methods is compared with lossless single-layer (SL) coding using the intra-main RExt configuration. Experimental results show that the scalable coding with SELC achieves average bitrate savings of 7.3% compared with the lossless SL coding, while average bitrate reductions of only 6.3% and 3.9% are obtained using JPEG-LS and SHVC, respectively. Concerning runtime, the additional encoder runtimes of SELC and JPEG-LS compared with the BL coding are negligible. In contrast to that, the runtime of the SHVC EL encoder is much higher and similar to the runtime of the BL encoder.

Sample-based Weighted Prediction for lossless enhancement layer coding in SHVC

Many professional applications require video content to be compressed in a lossless manner. However, often it is also advantageous to have access to a lossy coded version of the same video content, for example for preview purposes. In this paper the Sample-based Weighted Prediction (SWP) algorithm is applied for two-layer lossy to lossless scalable video compression with SHVC. This means that lossy compression is used for the first layer, the so-called base layer, and lossless compression is used for the second layer, also referred to as enhancement layer. In order to increase the coding efficiency of the enhancement layer the SWP algorithm is used for sample-wise prediction. Depending on the quantization parameter for the base layer, significant bitrate savings considering both layers of up to 8.38% (up to 6.20% on average) compared to the unmodified SHVC reference software can be achieved.

Analysis of prediction algorithms for residual compression in a lossy to lossless scalable video coding system based on HEVC

Lossless image and video compression is required in many professional applications. However, lossless coding results in a high data rate, which leads to a long wait for the user when the channel capacity is limited. To overcome this problem, scalable lossless coding is an elegant solution. It provides a fast accessible preview by a lossy compressed base layer, which can be refined to a lossless output when the enhancement layer is received. Therefore, this paper presents a lossy to lossless scalable coding system where the enhancement layer is coded by means of intra prediction and entropy coding. Several algorithms are evaluated for the prediction step in this paper. It turned out that Sample-based Weighted Prediction is a reasonable choice for usual consumer video sequences and the Median Edge Detection algorithm is better suited for medical content from computed tomography. For both types of sequences the efficiency may be further improved by the much more complex Edge-Directed Prediction algorithm. In the best case, in total only about 2.7% additional data rate has to be invested for scalable coding compared to single-layer JPEG-LS compression for usual consumer video sequences. For the case of the medical sequences scalable coding is even more efficient than JPEG-LS compression for certain values of QP.

Decoding-Energy-Rate-Distortion Optimization for Video Coding

This paper presents a method for generating coded video bit streams requiring less decoding energy than conventionally coded bit streams. To this end, we propose extending the standard rate-distortion optimization approach to also consider the decoding energy. In the encoder, the decoding energy is estimated during runtime using a feature-based energy model. These energy estimates are then used to calculate decoding-energy-rate-distortion costs that are minimized by the encoder. This ultimately leads to optimal tradeoffs between these three parameters. Therefore, we introduce the mathematical theory for describing decoding-energy-rate-distortion optimization and the proposed encoder algorithm is explained in detail. For rate-energy control, a new encoder parameter is introduced. Finally, measurements of the software decoding process for HEVC-coded bit streams are performed. Results show that this approach can lead to up to 30% of decoding energy reduction at a constant visual objective quality when accepting a bit rate increase at the same order of magnitude.

Formangepasste diskrete Cosinus-Transformation für die Prädiktionsverbesserung im HEVC

Um die Kompression in der Videocodierung zu verbessern, führen wir eine explizite Referenzbildentrauschung in die Codierschleife eines Videocodecs ein. Motiviert durch den Gedanken, dass die Leistung des Prädiktionsfehlers höher sein kann, falls Rauschen in dem zu codierenden Video vorhanden ist, wird die Bewegungskompensation durch die eingeführten Module verbessert. Es wird gezeigt wie man einen solchen Ansatz für die Codierung bei sehr kleinen Einstellungen des Quantisierungsparameters aber auch bei sehr groben Quantisierungseinstellungen verwenden kann. Die entwickelten Algorithmen wurden in der Referenzsoftware des aktuellen HEVC-Standards getestet. Die Simulationsergebnisse zeigen, dass mit der vorgeschlagenen Vorgehensweise maximale Bitratenersparnisse von bis zu 10 % für niedrige als auch hohe Quantisierungsparametereinstellungen erreicht werden können. Im Durchschnitt wurden Bitratenersparnisse von 7 % für hohe Qualität und 5 % für niedrige Qualität bei Codierung der ClassB-Sequenzen erreicht.