SBIR Phase II: Parallel Hardware Implementation of the Split and Merge Discrete Wavelet Transform for Wireless Communication

这项小型企业创新研究(SBIR)第二阶段项目建议开发基于离散小波变换(DWT)的新型图像压缩/信号分解算法的知识产权(IP)核心。这是JPEG2000 DWT引擎的完全并行、可扩展、多分辨率和低功耗实现，特别适合用于频谱一端的消费应用程序(如在下一代支持网络的手机中发现的无线通信信道上的降低比特率网络浏览)以及频谱另一端的高端商业应用程序(如电影行业的非线性视频编辑加速器)。这种特殊的实现是DWT变换的高效实现，并利用了一种新的重叠状态小波分解算法，该算法最大限度地减少了内存、I/O和计算需求。在接下来的十年里，消费者对在日益集成的地面和卫星系统上进行快速移动语音和IP通信的需求不断上升，受到有限的电磁频谱分配的困扰，因此有必要追求和开发更好的压缩算法，以在低比特率下实现视觉上的愉悦。作为广泛研究的结果，变换编码技术现在主导了迄今为止提出的每一种图像和视频编码方案。事实上，人们普遍认为JPEG2000将成为数字图像和高质量视频的普遍接受格式-无论是在网络、电缆、无线系统、数码相机、打印机、传真还是远程传感器中。凭借其基于小波的图像编码技术，它提供了以前在JPEG中无法实现的功能。与旧的基准JPEG相比，新的JPEG2000规范给无数开发人员和OEM计划使用它带来了巨大的技术挑战。新标准使用了基于离散小波变换(DWT)的编码算法，这与离散余弦变换(DCT)JPEG规范有根本的不同。在JPEG2000中，计算瓶颈(尤其是内存瓶颈)的重要性显然比旧规范增加了好几倍。事实上，近年来已经报道了各种计算效率较高的CE小波变换的实现。

This Small Business Innovative Research (SBIR) Phase II project proposes to develop the Intellectual Property (IP) core of a novel image compression / signal decomposition algorithm based on the discrete wavelet transform (DWT). This is a fully parallel, scalable, multi-resolution, and low power implementation of the JPEG2000 DWT engine and is particularly well suited for use in both consumer applications at one end of the spectrum (as in reduced bit-rate web browsing over wireless communications channels as found in the next generation of web enabled cell phones) as well as in high-end commercial applications at the other end of the spectrum (as in non-linear video editing accelerators for the movie industry). This particular implementation is a highly efficient implementation of the DWT transform and makes use of a novel Overlap-State wavelet decomposition algorithm which minimizes memory, I/O and computational requirements. Over the next decade, spiraling consumer demand for fast mobile communication of voice and IP over increasingly integrated terrestrial and satellite based systems plagued by a limited electro-magnetic spectrum allocation necessitates the pursuit and development of better compression algorithms that a visually pleasing at low bit rates. As a consequence of extensive research, transform coding techniques now dominate every single image and video coding scheme proposed to-date. Consequently, efficient software and hardware based transform coding system designs and implementations have become a high priority objective.In fact, it is widely accepted that JPEG2000 will become the universally accepted format for digital images and high quality video - whether on the web, cable, over wireless systems, in digital cameras, printers, faxes or remote sensors. With its wavelet based image-coding technology, it offers features previously impossible in JPEG. Compared with the old baseline JPEG, the new JPEG2000 spec poses formidable technology challenges for the myriad of developers and OEM's planning on using it. The new standard uses coding algorithms based on the discrete wavelet transform (DWT) which is fundamentally different from the discrete cosine transform (DCT) JPEG spec. In JPEG2000, the importance of computational and especially memory bottlenecks has clearly increased several fold over the old specification. In fact, various implementations of computationally efficientCE wavelet transforms have been reported in recent years.