Numerical Reconstruction and Compression of Thermal Image Sequences

Data compression and enhancement represent an important consideration in many application areas. The transmission bandwidth and storage capacity are often crucial factors. The efficiency of the processing of data in numerous cases strongly depends on the form of data representation. In the present paper a method, based on the so called higher order singular value decomposition and tensor-product transformation, is introduced for multidimensional scaling and compression of thermal images sequences. The proposed approach operates with smooth functions forming an orthonormal basis. Because of the smoothness property of these orthonormal components, the method can advantageously be utilized for the efficient compression of thermal image sequences.

I. Introduction

There are various applications, where large amount of data has to be transmitted in real-time or near real-time, e.g. surveillance systems, MRI imaging, etc. The transmission bandwidth and storage capacity are crucial factors, therefore the efficient representation and compression of data play important roles.