This paper presents a novel implementation of the JPEG2000 standard as a system on a chip (SoC). While most of the research in this field centers on acceleration of the EBCOT Tier I encoder, this work focuses on an embedded solution for EBCOT Tier II. Specifically, this paper proposes using an embedded softcore processor to perform Tier II processing as the back end of an encoding pipeline. The Altera NIOS II processor is chosen for the implementation and is coupled with existing embedded processing modules to realize a fully embedded JPEG2000 encoder. The design is synthesized on a Stratix IV FPGA and is shown to out perform other comparable SoC implementations by 39% in computation time.

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In this paper, an integer-based Cohen-Daubechies-Feauvea (CDF) 9/7 wavelet transform as well as an integer quantization method used in a lossy JPEG2000 compression engine is presented. The conjunction of both an integer transform and quantization step allows for a complete integer computation of lossy JPEG2000 compression. The lossy method of compression utilizes the CDF 9/7 wavelet filter, which transforms integer input pixel values into floating-point wavelet coefficients that are then quantized back into integers and finally compressed by the embedded block coding with optimal truncation tier-1 encoder. Integer computation of JPEG2000 allows a reduction in computational complexity of the wavelet transform as well as ease of implementation in embedded systems for higher computational performance. The results of the integer computation show an equivalent rate/distortion curve to the JasPer JPEG2000 compression engine, as well as a 30% reduction in computation time of the wavelet transform and a 56% reduction in computation time of the quantization processing on an average.

Integer-bmed Wavelet Transforms present advantages in image compression such as computational speed, simplicity, and reconstructed image quality. The nature of wavelet decomposition allows high compression ratios to be achieved through efficient methods of encoding. The work presented here describes an eficient hardware implementation of a simple integer-division algorithm for the quantization of image data using FPGAs. In addition, this paper presents an overview of the use of wavelet analysis and wavelet transforms, specijkally the Haar Wavelet Transform, in real-time image compression.

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