IntraPeriod : 60 # Period of I-Frame ( -1 = only first) HM14.0 Low Delay configuration snippet: #= Coding Structure = IntraPeriod : 64 # Period of I-Frame ( -1 = only first)ĭecodingRefreshType : 0 # Random Accesss 0:none, 1:CRA, 2:IDR, 3:Recovery Point SEI B-pyramid structure is used for higher quality: #= Coding Structure = HM14.0 Random Access configuration snippet. HM14.0 Tested command line: >TappEncoderStatic -c -f NUM_OF_FRAMES -fs 0 -fr FRAME_RATE -InputBitDepth=8|10 -OutputBitDepth=8|10 -wdt VIDEO_WIDTH -hgt VIDEO_HEIGHT -i INPUT_FILE_NAME -q QP_VALUE -b OUT_FILE_NAME Following is the tested execution command line and configuration for each encoder. GOP structure is defined by each encoder based on its capability while locking I frame Qp value and its period, as defined in Table 2, for fair comparison. Table 3: Video sequences and configuration definition. All the sequences are available to the public at. Input video sequences are defined in Table 3. Because configuration capability of GOP structure should be included for this quality assessment, we defined I frame Qp value and period as common conditions across target encoders. Qp offset for P frame and B frame including GOP (group of pictures) structure are defined by each encoder based on its capability. Table 2: Qp value and intra frame period definition. To avoid quality impact by rate controller implementations, we used constant Qp for each frame, as with standardized methodology. We defined 10 different Qp values for all the intra frames of this quality assessment to cover a wide range of bitrates. Smaller Qp value indicates larger frame size larger Qp value indicates smaller frame size. Transformed compressed video signals are quantized by using the Quantization Parameter (Qp). Frame re-ordering is required at the deciding stage in this configuration. The other configuration is Random Access (RA), which includes both forward and backward references for better quality. In this configuration, frame re-ordering is not required at the time of decoding so that the encoder and decoder frame order matches. One is Low Delay (LD), which has forward reference only to cover low latency use cases such as video conferencing. Two configurations are selected for this quality assessment to cover various encoding use cases. ffmpeg-4.1.3-win64-static.zip (2019-Apr-26 16:10)Ĭonfigurations-Low Delay and Random Access We used three encoders for this quality assessment as shown in the following table.ġ0th generation Intel® Core™ processor and Intel® Media SDK sample encode 2 Based on this methodology, we defined the following configurations and conditions and used HM Test Model 3 as an anchor encoder software. We used standardized methodology that has been used by video coding standardization groups such as JCTVC. In order to conduct video quality assessment fairly, common conditions and software configurations need to be defined across encoders. This paper addresses HEVC hardware encoding quality evaluation delivered by 10th generation Intel Core processors by using industry standard methodology. In the 10th generation Intel Core processor, video quality of HEVC hardware encoding is dramatically improved by implementing new logic. Intel has been a leader in striving for these difficulties for a decade starting with the 1st generation Intel Core processor, and continuously improving encoding quality, performance, and configuration flexibility. On the other hand, hardware-based encoding tends to have different challenges in terms of quality and configuration flexibility, as compared to software-based solutions. Software-based encoding takes a significant amount of time or consumes a lot of power, which has big impact on battery life in laptop or mobile use cases. Video compression is a highly complex process defined by international standards. The analysis includes video encode quality of HEVC 1 codecs using objective evaluation methodology. This paper provides the status quo of video encode quality of a key revision to Intel Codec IP available in 10th generation Intel® Core™ processors. Cloud-based video distribution and video analytics workloads are growing exponentially. Video compression technologies play a key role in creation and distribution of high-quality video content. Achieve efficient, flexible, and faster media creation and distribution with high quality and high performance hardware encoder.
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