Low power H.264 video compression hardware designs

Video compression systems are used in many commercial products such as digital camcorders, cellular phones and video teleconferencing systems. H.264 / MPEG4 Part 10, the recently developed international standard for video compression, offers significantly better video compression efficiency than previous international standards. However, this coding gain comes with an increase in encoding complexity and therefore in power consumption. Since portable devices operate with battery, it is important to reduce power consumption so that the battery life can be increased. In addition, consuming excessive power degrades the performance of integrated circuits, increases packaging and cooling costs, reduces the reliability and may cause device failures. Therefore, power consumption is an important design metric for video compression hardware. In this thesis, we propose low power hardware designs for Deblocking Filter (DBF), intra prediction and intra mode decision parts of an H.264 video encoder. The proposed hardware architectures are implemented in Verilog HDL and mapped to Xilinx Virtex II FPGA. We performed detailed power consumption analysis of FPGA implementations of these hardware designs using Xilinx XPower tool. We also measured the power consumptions of DBF hardware implementations on a Xilinx Virtex II FPGA and there is a good match between estimated and measured power consumption results. We then worked on decreasing the power consumption of FPGA implementations of these H.264 video compression hardware designs by reducing switching activity using Register Transfer Level (RTL) low power techniques. We applied several RTL low power techniques such as clock gating and glitch reduction to these designs and quantified their impact on the power consumption of the FPGA implementations of these designs. We proposed novel computational complexity and power reduction techniques which avoid unnecessary calculations in DBF, intra prediction and intra mode decision parts of an H.264 video encoder. We quantified the computation reductions achieved by the proposed techniques using H.264 Joint Model software encoder. We applied these techniques to proposed hardware designs and quantified their impact on the power consumption of the FPGA implementations of these designs

A High performance and low cost hardware arcitecture for H.264 transform and quantization algorithms

In this paper, we present a high performance and low cost hardware architecture for real-time implementation of forward transform and quantization and inverse transform and quantization algorithms used in H.264 / MPEG4 Part 10 video coding standard. The hard-ware architecture is based on a reconfigurable datapath with only one multiplier. This hardware is designed to be used as part of a complete low power H.264 video coding system for portable appli-cations. The proposed architecture is implemented in Verilog HDL. The Verilog RTL code is verified to work at 81 MHz in a Xilinx Virtex II FPGA and it is verified to work at 210 MHz in a 0.18´ ASIC implementation. The FPGA and ASIC implementations can code 27 and 70 VGA frames (640x480) per second respectively

Dynamically Reconfigurable Architectures and Systems for Time-varying Image Constraints (DRASTIC) for Image and Video Compression

In the current information booming era, image and video consumption is ubiquitous. The associated image and video coding operations require significant computing resources for both small-scale computing systems as well as over larger network systems. For different scenarios, power, bitrate and image quality can impose significant time-varying constraints. For example, mobile devices (e.g., phones, tablets, laptops, UAVs) come with significant constraints on energy and power. Similarly, computer networks provide time-varying bandwidth that can depend on signal strength (e.g., wireless networks) or network traffic conditions. Alternatively, the users can impose different constraints on image quality based on their interests. Traditional image and video coding systems have focused on rate-distortion optimization. More recently, distortion measures (e.g., PSNR) are being replaced by more sophisticated image quality metrics. However, these systems are based on fixed hardware configurations that provide limited options over power consumption. The use of dynamic partial reconfiguration with Field Programmable Gate Arrays (FPGAs) provides an opportunity to effectively control dynamic power consumption by jointly considering software-hardware configurations. This dissertation extends traditional rate-distortion optimization to rate-quality-power/energy optimization and demonstrates a wide variety of applications in both image and video compression. In each application, a family of Pareto-optimal configurations are developed that allow fine control in the rate-quality-power/energy optimization space. The term Dynamically Reconfiguration Architecture Systems for Time-varying Image Constraints (DRASTIC) is used to describe the derived systems. DRASTIC covers both software-only as well as software-hardware configurations to achieve fine optimization over a set of general modes that include: (i) maximum image quality, (ii) minimum dynamic power/energy, (iii) minimum bitrate, and (iv) typical mode over a set of opposing constraints to guarantee satisfactory performance. In joint software-hardware configurations, DRASTIC provides an effective approach for dynamic power optimization. For software configurations, DRASTIC provides an effective method for energy consumption optimization by controlling processing times. The dissertation provides several applications. First, stochastic methods are given for computing quantization tables that are optimal in the rate-quality space and demonstrated on standard JPEG compression. Second, a DRASTIC implementation of the DCT is used to demonstrate the effectiveness of the approach on motion JPEG. Third, a reconfigurable deblocking filter system is investigated for use in the current H.264/AVC systems. Fourth, the dissertation develops DRASTIC for all 35 intra-prediction modes as well as intra-encoding for the emerging High Efficiency Video Coding standard (HEVC)

VHDL Modeling of an H.264/AVC Video Decoder

Transmission and storage of video data has necessitated the development of video com pression techniques. One of today\u27s most widely used video compression techniques is the MPEG-2 standard, which is over ten years old. A task force sponsored by the same groups that developed MPEG-2 has recently finished defining a new standard that is meant to replace MPEG-2 for future video compression applications. This standard, H.264/AVC, uses significantly improved compression techniques. It is capable of providing similar pic ture quality at bit rates of 30-70% less than MPEG-2, depending on the particular video sequence and application [20]. This thesis developed a complete VHDL behavioral model of a video decoder imple menting the Baseline Profile of the H.264/AVC standard. The decoder was verified using a testing environment for comparison with reference software results. Development of a synthesizable hardware description was also shown for two components of the video de coder: the transform unit and the deblocking filter. This demonstrated how a complete video decoder could be developed one module at a time with individual module verifica tion. Analysis was also done to estimate the performance and hardware requirements for a complete implementation on an FPGA device

Network-on-Chip Based H.264 Video Decoder on a Field Programmable Gate Array

This thesis develops the first fully network-on-chip (NoC) based h.264 video decoder implemented in real hardware on a field programmable gate array (FPGA). This thesis starts with an overview of the h.264 video coding standard and an introduction to the NoC communication paradigm. Following this, a series of processing elements (PEs) are developed which implement the component algorithms making up the h.264 video decoder. These PEs, described primarily in VHDL with some Verilog and C, are then mapped to an NoC which is generated using the CONNECT NoC generation tool. To demonstrate the scalability of the proposed NoC based design, a second NoC based video decoder is implemented on a smaller FPGA using the same PEs on a more compact NoC topology. The performance of both decoders, as well as their component PEs, is evaluated on real hardware. An analysis of the performance results is conducted and recommendations for future work are made based on the results of this analysis. Aside from the development of the proposed decoder, a major contribution of this thesis is the release of all source materials for this design as open source hardware and software. The release of these materials will allow other researchers to more easily replicate this work, as well as create derivative works in the areas of NoC based designs for FPGA, video coding and decoding, and related areas

Dynamic Switching of GOP Configurations in High Efficiency Video Coding (HEVC) using Relational Databases for Multi-objective Optimization

Our current technological era is flooded with smart devices that provide significant computational resources that require optimal video communications solutions. Optimal and dynamic management of video bitrate, quality and energy needs to take into account their inter-dependencies. With emerging network generations providing higher bandwidth rates, there is also a growing need to communicate video with the best quality subject to the availability of resources such as computational power and available bandwidth. Similarly, for accommodating multiple users, there is a need to minimize bitrate requirements while sustaining video quality for reasonable encoding times. This thesis focuses on providing an efficient mechanism for deriving optimal solutions for High Efficiency Video Coding (HEVC) based on dynamic switching of GOP configurations. The approach provides a basic system for multi-objective optimization approach with constraints on power, video quality and bitrate. This is accomplished by utilizing a recently introduced framework known as Dynamically Reconfigurable Architectures for Time-varying Image Constraints (DRASTIC) in HEVC/H.265 encoder with six different GOP configurations to support optimization modes for minimum rate, maximum quality and minimum computational time (minimum energy in constant power configuration) mode of operation. Pareto-optimal GOP configurations are used in implementing the DRASTIC modes. Additionally, this thesis also presents a relational database formulation for supporting multiple devices that are characterized by different screen resolutions and computational resources. This approach is applicable to internet-based video streaming to different devices where the videos have been pre-compressed. Here, the video configuration modes are determined based on the application of database queries applied to relational databases. The database queries are used to retrieve a Pareto-optimal configuration based on real-time user requirements, device, and network constraints

Efficient hardware implementations of low bit depth motion estimation algorithms

In this paper, we present efficient hardware implementation of multiplication free one-bit transform (MF1BT) based and constraint one-bit transform (C-1BT) based motion estimation (ME) algorithms, in order to provide low bit-depth representation based full search block ME hardware for real-time video encoding. We used a source pixel based linear array (SPBLA) hardware architecture for low bit depth ME for the first time in the literature. The proposed SPBLA based implementation results in a genuine data flow scheme which significantly reduces the number of data reads from the current block memory, which in turn reduces the power consumption by at least 50% compared to conventional 1BT based ME hardware architecture presented in the literature. Because of the binary nature of low bit-depth ME algorithms, their hardware architectures are more efficient than existing 8 bits/pixel representation based ME architectures

Methodology and optimizing of multiple frame format buffering within FPGA H.264/AVC decoder with FRExt.

Digital representation of video data is an inherently resource demanding problem that continues to necessitate the development and refinement of coding methods. The H.264/AVC standard, along with its recent Fidelity Range Extensions amendment (FRExt), is quickly being adopted as the standard codec for broadcast and distribution of high definition video. The FRExt amendment, while not necessarily affecting the overall decoder architecture, presents an added complexity of providing efficient memory management for buffering intermediate frames of various pixel color samplings and depths. This thesis evaluated the role of designing the frame buffer of a hardware video decoder, with integrated support for the H.264/AVC codec plus FRExt. With focus on organizing external memory data access, the frame buffer was designed to provide intermediate data storage for the decoder, while using an efficient store and load scheme that takes into consideration each frame pixel format of the video data. VHDL was used to model the frame buffer. Exploitation of reconfigurability and post-synthesis FPGA simulations were used to evaluate behavior, scalability and power consumption, while providing an analysis of approaches to adding FRExt to the memory management. Real-time buffer performance was achieved for two common frame formats at 1080 HD resolution; and an innovative pipeline design provides dynamic switching of formats between video sequences. As an additional consequence of verifying the model, a preexisting Baseline H.264/AVC decoder testbench was augmented to support testing of multiple frame formats