This paper presents efficient SIMD optimizations for the open-source Kvazaar HEVC intra encoder. The C implementation of Kvazaar is accelerated by Intel AVX2 instructions whose effect on Kvazaar ultrafast preset is profiled. According to our profiling results, C functions of SATD, DCT, quantization, and intra prediction account for over 60% of the total intra coding time of Kvazaar ultrafast preset. This work shows that optimizing primarily these functions doubles the coding speed of a single-threaded Kvazaar intra encoder for the same rate-distortion performance. The highest performance boost is obtained by deploying the proposed optimizations jointly with multithreading. On the Intel 8-core i7 processor, the AVX2-optimized 16-threaded Kvazaar ultrafast preset achieves real-time (30 fps) intra coding speed up to 1080p resolution. Compared to AVX2-optimized ultrafast preset of x265, Kvazaar is 20% times faster and still obtains 9.1% bit rate gain for the same quality. These results justify that Kvazaar is currently the leading open-source HEVC intra encoder in terms of real-time coding speed and efficiency.

This demonstrator presents a run-time visualization tool for Kvazaar HEVC intra encoder. The implemented open-source tool is seamlessly integrated into Kvazaar to provide instant visual feedback of the encoding process. The visualization overlays the reconstructed HEVC video with the boundaries of the used block partitioning structure and associated intra prediction modes. The tool is also able to illustrate all Kvazaar parallelization schemes at run time: Wavefront Parallel Processing, tiles, and picture-level parallel processing. The displayed visualization information can be gradually adjusted to user needs. The tool is primarily designed for Kvazaar debugging but it also suits educational purposes.

Kvazaar is an academic software video encoder for the emerging High Efficiency Video Coding (HEVC/H.265) standard. It provides students, academic professionals, and industry experts a free, cross-platform HEVC encoder for x86, x64, PowerPC, and ARM processors on Windows, Linux, and Mac. Kvazaar is being developed from scratch in C and optimized in Assembly under the LGPLv2.1 license. The development is being coordinated by Ultra Video Group at Tampere University of Technology (TUT) and the implementation work is carried out by an active community on GitHub. Developer friendly source code of Kvazaar makes joining easy for new developers. Currently, Kvazaar includes all essential coding tools of HEVC and its modular source code facilitates parallelization on multi and manycore processors as well as algorithm acceleration on hardware. Kvazaar is able to attain real-time HEVC coding speed up to 4K video on an Intel 14-core Xeon processor. Kvazaar is also supported by FFmpeg and Libav. These de-facto standard multimedia frameworks boost Kvazaar popularity and enable its joint usage with other well-known multimedia processing tools. Nowadays, Kvazaar is an integral part of teaching at TUT and it has got a key role in three Eureka Celtic-Plus projects in the fields of 4K TV broadcasting, virtual advertising, Video on Demand, and video surveillance.

This paper presents an open-source Kvazaar encoder for HEVC intra coding. This academic software encoder has been developed from the scratch using C as an implementation language by prioritizing modularity, portability, and readability of the source code. Kvazaar implements almost the same intra coding functionality as HEVC reference encoder (HM) but its rewritten source code makes it significantly faster. In all-intra (AI) coding, a single-threaded C implementation of Kvazaar is 2.3 times faster than HM at a cost of 1.7% bit rate increase. The respective values with a high speed preset of Kvazaar are 10.6 and 8.8%. Compared to a single-threaded C++ implementation of x265, Kvazaar improves rate-distortion performance and increases encoding speed in both high-quality and high-speed test cases. Kvazaar has a particular edge in the high-speed test case where it almost halves the BD-rate loss and more than doubles the performance.

This demonstrator serves as a proof-of-concept of our multi-camera remote surveillance system that supports 1080p still image capture with a 10-second refresh rate. Image capture, compression, and broadcast are implemented in each Raspberry Pi 2 camera node. Image compression is conducted with an open-source Kvazaar HEVC encoder that outputs HEVC images in BPG format. The BPG images are broadcast from camera nodes to terminals over the Internet through WebSocket protocol. The images can be played back with most Web browsers in remote locations with Internet access.

This paper compares the rate-distortion-complexity (RDC) characteristics of the HEVC Main 10 Profile (M10P) and Main Profile (MP) encoders. The evaluations are performed with HEVC reference encoder (HM) whose M10P and MP are benchmarked with different resolutions, frame rates, and bit depths. The reported RD results are based on bit rate differences for equal PSNR whereas complexities have been profiled with Intel VTune on Intel Core 2 processor. With our 10-bit 4K 120 fps test set, the average bit rate decrements of M10P over MP are 5.8%, 11.6%, and 12.3% in the all-intra (AI), random access (RA), and low-delay B (LB) configurations, respectively. Decreasing the bit depth of this test set to 8 lowers the RD gain of Ml OP only slightly to 5.4% (AI), 11.4% (RA), and 12.1% (LB). The similar trend continues in all our tests even though the RD gain of M10P is decreased over MP with lower resolutions and frame rates. M10P introduces no computational overhead in HM, but it is anticipated to increase complexity and double the memory usage in practical encoders. Hence, the 10-bit HEVC encoding with 8-bit input video is the most recommended option if computation and memory resources are adequate for it.