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Design of multiplierless, high-performance, wavelet filter banks with image compression applications

机译:具有图像压缩应用的无倍数高性能小波滤波器组的设计

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The JPEG2000 image coding standard employs the biorthogonal 9/7 wavelet for lossy compression. The performance of a hardware implementation of the 9/7 filter bank depends on the accuracy and the efficiency with which the quantized filter coefficients are represented. A high-precision representation ensures compression performance close to the unquantized, infinite precision filter bank, but at the cost of increased hardware resources and processing time. If the filter coefficients are quantized such that the filter bank properties are preserved, then, the degradation in compression performance will be minimal. This paper investigates two filter structures and two "compensating" filter coefficient quantization methods for improving the performance of multiplierless, quantized filter banks. Rather than using an optimization technique to guide the design process, the new methods utilizes the perfect reconstruction requirements of the filter bank. The results indicate that the best method (a cascade structure with compensating zeros) realizes image-compression performance very similar to the unquantized filter case while also achieving a fast, efficient hardware implementation.
机译:JPEG2000图像编码标准采用双正交9/7小波进行有损压缩。 9/7滤波器组的硬件实现的性能取决于表示量化滤波器系数的准确性和效率。高精度表示可确保压缩性能接近未量化的无限精度滤波器组,但以增加硬件资源和处理时间为代价。如果对滤波器系数进行量化以使滤波器组属性得以保留,则压缩性能的下降将最小。本文研究了两种滤波器结构和两种“补偿”滤波器系数量化方法,以提高无乘法器,量化滤波器组的性能。新方法没有使用优化技术来指导设计过程,而是利用了滤波器组的完美重建要求。结果表明,最佳方法(具有零补偿的级联结构)实现的图像压缩性能与未量化的滤波器情况非常相似,同时还实现了快速,高效的硬件实现。

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