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    • 1. 发明授权
    • Fast multiplierless integer invertible transforms
    • 快速无乘法整数可逆转换
    • US08548265B2
    • 2013-10-01
    • US11649491
    • 2007-01-04
    • Trac D. TranPankaj N. Topiwala
    • Trac D. TranPankaj N. Topiwala
    • G06K9/36
    • H04N19/42G06F17/147H04N19/45H04N19/61
    • This invention relates to the design and implementation of a large family of fast, efficient, hardware-friendly fixed-point multiplierless inverse discrete cosine transforms (IDCT) and the corresponding forward transform counterparts. All of the proposed structures comprises of butterflies and dyadic-rational lifting steps that can be implemented using only shift-and-add operations. The approach also allows the computational scalability with different accuracy-versus-complexity trade-offs. Furthermore, the lifting construction allows a simple construction of the corresponding multiplierless forward DCT, providing bit-exact reconstruction if properly pairing with our proposed IDCT. With appropriately-chosen parameters, all of the disclosed structures can easily pass IEEE-1180 test. The high-accuracy algorithm of the present invention is over 100 times more accurate than IEEE-1180 specifications, leading to practically drifting-free reconstruction in popular MPEG-2 and MPEG-4 codecs even at the lowest quantization setting.
    • 本发明涉及一系列快速,高效,硬件友好的定点无乘法反相离散余弦变换(IDCT)和相应的正向变换对等体的设计与实现。 所有提出的结构都包括蝴蝶和二元合理的提升步骤,可以使用移位和加法操作来实现。 该方法还允许具有不同准确度与复杂度权衡的计算可扩展性。 此外,提升结构允许相应的无乘法正向DCT的简单构造,如果与我们提出的IDCT正确配对,则提供比特精确重构。 通过适当选择的参数,所有公开的结构可以轻松通过IEEE-1180测试。 本发明的高精度算法比IEEE-1180规范精度高出100多倍,即使在最低的量化设置下,也能在流行的MPEG-2和MPEG-4编解码器中实现无漂移重建。
    • 2. 发明授权
    • Method for local zerotree image coding
    • 局部零树图像编码方法
    • US06771829B1
    • 2004-08-03
    • US09694202
    • 2000-10-23
    • Pankaj N. TopiwalaTrac D. Tran
    • Pankaj N. TopiwalaTrac D. Tran
    • G06K936
    • H04N19/17H04N19/127H04N19/129H04N19/63H04N19/647
    • A transform-based image compression framework called local zerotree (LZT) coding partitions the transform coefficients into small groups, each of which is encoded independently using popular zerotree algorithms. The LZT coder achieves similar coding performances as current state-of-the-art embedded coders. The advantage of this coding method is fourfold: (i) because of the reduction of memory buffering, LZT reduces the complexity of the codec implementation and increase the speed of the zerotree algorithm significantly, especially in hardware; (ii) LZT processes large images under limited memory constraint; (iii) LZT supports parallel processing mode as long as the transform in use has that capability; and (iv) LZT facilitates the coding/decoding of regions of interest. The penalty in coding performance is minute compared to global zerotree predecessors in that there are only a few extra bytes of side information. This new coder provides numerous other advantages: faster and simpler hardware implementation, supporting parallel processing mode, facilitating region-of-interest coding/decoding, and capable of processing large images under limited memory constraint. The only properties that LZT sacrifices are full embeddedness and progressive transmission.
    • 基于变换的图像压缩框架称为局部零树(LZT)编码,将变换系数分为小组,每一个都使用流行的零树算法独立编码。 LZT编码器实现与当前最先进的嵌入式编码器相似的编码性能。 这种编码方法的优点有四个方面:(1)由于存储缓存的减少,LZT降低了编解码器实现的复杂度,显着提高了零树算法的速度,特别是在硬件方面; (ii)LZT在有限的记忆限制下处理大图像; (iii)LZT支持并行处理模式,只要使用中的转换具有该功能; 和(iv)LZT有助于感兴趣区域的编码/解码。 与全局零树前辈相比,编码性能的惩罚是微不足道的,因为只有少量额外字节的边信息。 这种新的编码器提供了许多其他优点:更快更简单的硬件实现,支持并行处理模式,便于感兴趣的区域编码/解码,并且能够在有限的存储器限制下处理大图像。 LZT牺牲的唯一属性是完全嵌入和逐行传输。