Preliminary analysis of noisy image lossy compression by discrete atomic transform-based coder

Abstract

Remote sensing provides data (images) important for many modern applications. Image number and average size tend to increase. This makes their transfer via communication lines, storage, and dissemination problematic. Thus, compression should be applied where lossy compression is mostly used. Most methods of lossy compression assume that images do not contain noise. Meanwhile, images are often noisy, and this should be considered in the design and performance analysis of image compression techniques. Lossy compression has already been studied by several coders. However, it has not been investigated for the recently proposed atomic transform-based techniques that possess several advantages, in particular, the ability to provide privacy of compressed data. The main subject of this paper is the peculiarities of noisy image lossy compression by an atomic transform-based coder. Our goal is to analyze whether the considered compression method provides the noise filtering effect and the so-called optimal operation point. The task is to obtain rated distortion curves for the atomic transform-based coder applied to noisy images and to analyze their behavior for several performance characteristics such as quality metrics and compression ratio. In the first order, the monotonicity of the main dependence is of interest. The main results are as follows. First, it is shown that the dependencies have non-monotonic behavior and the appearance of analogs of optimal operation point is possible, at least, for such metric as maximal absolute error. Second, there is a specific dependence of compression ratio on a parameter called UBMAD that controls compression. Experiments have been performed on several noisy test images having different complexity and contaminated by noise of different intensities. In conclusion, it is demonstrated that one more coder might have optimal operation points for images having a rather simple structure. However, at the moment, it is difficult to predict its existence and the corresponding coder parameters.