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

SBIR 第二阶段：无线通信中分离与合并离散小波变换的并行硬件实现

• 批准号: 0239330
• 负责人: Alexander Moopenn
• 金额: $ 50万
• 依托单位: Mosaix, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-03-15 至 2005-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0239330&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Parallel; Hardware

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.

这个小型企业创新研究（SBIR）第二阶段项目提出了开发一种新的图像压缩/信号分解算法的知识产权（IP）核心的基础上离散小波变换（DWT）。这是一个完全并行、可扩展、多分辨率、和低功耗实现的JPEG 2000 DWT引擎，特别适合在消费者应用中使用的频谱的一端（如在下一代支持web的蜂窝电话中发现的通过无线通信信道的降低比特率的web浏览）以及在频谱的另一端的高端商业应用中（如在用于电影工业的非线性视频编辑加速器中）。这种特殊的实现是一种高效的实现的DWT变换，并利用一种新的重叠状态小波分解算法，最大限度地减少内存，I/O和计算的要求。在下一个十年中，消费者对在日益集成的基于陆地和卫星的系统上进行语音和IP的快速移动的通信的螺旋式增长的需求受到有限的电磁频谱分配的困扰，这需要追求和开发在低比特率下视觉上令人愉悦的更好的压缩算法。作为广泛研究的结果，变换编码技术现在主导了迄今提出的每一个图像和视频编码方案。事实上，人们普遍认为JPEG 2000将成为数字图像和高质量视频的普遍接受的格式-无论是在网络、电缆、无线系统、数码相机、打印机、传真机或远程传感器上。凭借其基于小波的图像编码技术，它提供了以前在JPEG中不可能实现的功能。与旧的JPEG标准相比，新的JPEG 2000标准对众多的开发者和计划使用它的OEM提出了巨大的技术挑战。新标准使用基于离散小波变换（DWT）的编码算法，这与离散余弦变换（DCT）JPEG标准有着根本的不同。在JPEG 2000中，计算和特别是存储器瓶颈的重要性明显地比旧规范增加了数倍。事实上，近年来已经报道了各种计算效率CE小波变换的实现。