Range and error analysis for a fast Fourier transform computed over Zω
IEEE Transactions on Information Theory
An Asynchronous Dataflow FPGA Architecture
IEEE Transactions on Computers
The H.264 Video Coding Standard
IEEE MultiMedia
Integer DCT based on direct-lifting of DCT-IDCT for lossless-to-lossy image coding
IEEE Transactions on Image Processing
The H.264 Advanced Video Compression Standard
The H.264 Advanced Video Compression Standard
High dynamic range for contrast enhancement
IEEE Transactions on Consumer Electronics
Low-complexity 8-point DCT approximations based on integer functions
Signal Processing
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Transformation and quantization play a critical role in video codecs. Recently proposed algebraic-integer-(AI-) based discrete cosine transform (DCT) algorithms are analyzed in the presence of quantization, using the High Efficiency Video Coding (HEVC) standard. AI DCT is implemented and tested on asynchronous quasi delay-insensitive logic, using Achronix SPD60 field programmable gate array (FPGA), which leads to lower complexity, higher speed of operation, and insensitivity to process-voltagetemperature variations. Performance of AI DCT with HEVC is measured in terms of the accuracy of the transform coefficients and the overall rate-distortion (R-D) characteristics, using HM 7.1 reference software. Results indicate a 31% improvement over the integer DCT in the number of transformcoefficients having error within 1%. The performance of the 65 nmasynchronous hardware in terms of speed of operation is investigated and compared with the 65 nm synchronous Xilinx FPGA. Considering word lengths of 5 and 6 bits, a speed increase of 230% and 199% is observed, respectively. These results indicate that AI DCT can be potentially utilized in HEVC for applications demanding high accuracy as well as high throughput. However, novel quantization schemes are required to allow the accuracy improvements obtained.