A novel multiresolution algorithm for lossy gray-scale image compression is presented. High-quality low bit rate image compression is achieved first by segmenting an image into regions of different sizes based on perceptual variation in each region and then constructing a distinct code for each block by using the theory of projection pursuit (PP). Projection pursuit allows one to adaptively construct a better approximation for each block by optimally selecting basis functions. The process is stopped when the desired peak signal-to-noise ratio (PSNR) or bit rate (b/pixel) is achieved. At rates below 0.5 b/pixel, our algorithm shows superior performance, both in terms of PSNR and subjective image quality, over the Joint Photographers Expert Group (JPEG) algorithm, and comparable performance to the embedded zerotree wavelet (EZW) algorithm.
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机译:提出了一种新颖的有损灰度图像压缩的多分辨率算法。高质量的低比特率图像压缩首先通过基于每个区域的感知变化将图像划分为不同大小的区域,然后使用投影追踪(PP)理论为每个块构造一个不同的代码来实现。投影追踪允许通过最佳选择基函数为每个块自适应地构建更好的近似值。当达到所需的峰值信噪比(PSNR)或比特率(b /像素)时,该过程将停止。在低于0.5 b /像素的速率下,我们的算法在PSNR和主观图像质量方面均表现出优于联合摄影师专家组(JPEG)算法的性能,并且与嵌入式零树小波(EZW)算法具有可比的性能。
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