Reiter E
Aware, Inc., Bedford, MA, USA.
Telemed J. 1996 Summer;2(2):131-7. doi: 10.1089/tmj.1.1996.2.131.
Wavelet compression is a transform-based compression technique recently shown to provide diagnostic-quality images at compression ratios as great as 30:1. Based on a recently developed field of applied mathematics, wavelet compression has found success in compression applications from digital fingerprints to seismic data. The underlying strength of the method is attributable in large part to the efficient representation of image data by the wavelet transform. This efficient or sparse representation forms the basis for high-quality image compression by providing subsequent steps of the compression scheme with data likely to result in long runs of zero. These long runs of zero in turn compress very efficiently, allowing wavelet compression to deliver substantially better performance than existing Fourier-based methods. Although the lack of standardization has historically been an impediment to widespread adoption of wavelet compression, this situation may begin to change as the operational benefits of the technology become better known.
小波压缩是一种基于变换的压缩技术，最近的研究表明，该技术能以高达30:1的压缩比提供具有诊断质量的图像。基于最近发展起来的应用数学领域，小波压缩已在从数字指纹到地震数据等压缩应用中取得成功。该方法的潜在优势在很大程度上归因于小波变换对图像数据的高效表示。这种高效或稀疏表示通过为压缩方案的后续步骤提供可能产生长串零的数据，构成了高质量图像压缩的基础。这些长串零反过来又能非常有效地被压缩，使得小波压缩比现有的基于傅里叶的方法具有显著更好的性能。尽管历史上缺乏标准化一直是小波压缩广泛应用的障碍，但随着该技术的操作优势被更多人了解，这种情况可能会开始改变。
