IMAGE PROCESSING FOR SECURITY APPLICATIONS: DOCUMENT RECONSTRUCTION AND VIDEO ENHANCEMENT

The co-occurrence matrix tool describes the spatial distribution of high and low dynamics images by means of a visual representation as well as of a number of numerical features. The second measure we developed focuses on the local contrast feature. Based on the local contrast, noise, details and homogeneous parts can be separated. An algorithm which is able in particular to enhance the details part is considered to perform well according to this measure. A third methodology for assessing the enhancement algorithm performance is to setup an experimental environment where the luminosity can be varied. The same scene can then be acquired with good luminosity (reference images) or under poor lighting conditions (images to be processed by the algorithms). In this case a good algorithm, given the badly illuminated images, would output images with a low distance from the reference image. To summarize, the main original contributions of this thesis in the field of image and video enhancement are the following: 1. the LARS algorithm has been improved for surveillance and vehicle driving assistance applications (and an FPGA implementation has been proposed); 2. three novel objective quality measures to assess the performance of dynamics reduction algorithms have been developed.