The thesis composes conventional and modern methods for digital scene capturing. The target of the thesis is a comparison of CMOS with Bayer mask and Foveon X3 Merrill sensors followed by a design of algorithms for image fusion which can combine advantages of the both sensor types. The thesis starts with an introduction and a description of methods and processes leading to scene capturing. The next part deals with capturing a gallery of test images and with a comparison of both sensors based on the gallery images. Further there are algorithms designed for image fusion which can combine advantages of the selected sensors. The last part of the thesis is devoted to an evaluation of results and of the used algorithms.

Mathematical morphology stems from set theory and it makes use of properties of point sets. The first point set is an origin image and the second one (usually smaller) is a structuring element. Morphological image transformations are image to image transformations based on a few elementary set operators. Fundamental morphologic operations are dilation, erosion and hit or miss. Next operations described in this work are opening and closing. Originally morphological operators were used for binary images only, later they were generalized for grey tone and color ones. This work describes the basic morphological image processing methods including their practical usage in image filtering and segmentation.