Comparative Study of Image Compression Techniques for Digital Particle Image Velocimetry

Abstract

A comparative, quantitative study of image compression techniques for use with digital particle image velocimetry has been performed. Several candidate compression algorithms were selected for the study including a lossless technique and a series of mathematical transform-based methods. Each of the compression algorithms was implemented using commercial off-the-shelf software packages. Three image sequences were selected to exercise the various compression methods. These sequences included a set of industry standard images and two sets of images obtained from experimental work conducted at NASA Langley. Evaluation of the various methods was accomplished using quantitative perceptual and metrological performance measures. The results of the study indicate that several methods of compression are applicable to digital particle image velocimetry images. For selected applications where thresholding of the image gray levels can be performed, lossless algorithms yield excellent performance in terms of compression rates and introduction of negligible errors to the images. For applications where thresholding is not appropriate, JPEG and wavelet-based algorithms yield high compression rates with minor spatial errors introduced to the images. Fractal-based algorithms were shown to be capable of providing high compression rates, but the technique must be guided via the use of a suitably selected template image if spatial errors are to be minimized in the compressed images.