This paper presents a novel fusion method which is based on background brightness adjustment for multiple medical
microscopic images. In this process, the background of each microscopic image is separated using the intensity
histogram of the image in HSI color space firstly. The ratio and the difference between a selected reference intensity and
the average background intensity of each image are calculated. Then, according to the ratio and the difference, the
intensity and the saturation of each image are adjusted respectively. Finally, the overlap region between adjacent images
is fused by linearly variable weights in RGB color space. The results of experiments indicate that the method can
availably remove the differences in brightness and color between images, and generate a satisfactory mosicked image.
In this paper we present a novel self-organizing shape from shading method based on hybrid reflection model which
includes diffuse and specular reflection components. Using this method, the shape of an object surface is recovered in
two steps. Firstly, a grayscale image of the surface is separated into diffuse and specular components, and a new image
only composed of diffuse component is created. Secondly, a self-organizing shape from shading algorithm is performed
for the new image, and the 3D shape of the surface is generated. The experimental results for synthetic and real images
demonstrate the availability and feasibility of our method.