This paper describes a research which attempts to combine the advantages of human analysts and computer automated processing for efficient human computer symbiosis in geospatial data fusion. Specifically, experiments performed were related to the analysis of the potential use of inhomogeneous (composed of different sources) stereo pairs for mapping dataset actualization. Inhomogeneous stereo pa...

In this work, we synthesize normals and color to add geometric details to an RGBN image (image with a color and a normal channel). Existing modeling and image processing tools are not apt to edit RGBN images directly. Since high resolution RGBN images can be obtained using photometric stereo, we used them as full models and as exemplars in a Texture from Example synthesis. Our method works on R...

A parallel stereo matching algorithm is presented which is mainly thought for the processing of images from pushbroom stereo cameras. The algorithm is designed for non-epipolar geometry, because of disturbances of flight attitude and velocity. Existing epipolar algorithms can give a first estimation of disparities in epipolar (x-) direction, but the recursive algorithm can also start with zero-...

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised ...

Due to a high percentage of the bad pixels in small baseline stereo matching method, a small baseline stereo matching method based on adaptive weight is proposed. Firstly, the size of reference window is adaptively calculated for each reference point and then matching costs is evaluated according to adaptive weights and reference window size. Secondly, winner take all is used to evaluate initia...

Most of the existing stereo matching algorithms assume that the corresponding pixels have the same intensity (color) in both images. But in real world situations, image color values are often affected by various radiometric factors such as illumination direction, illuminant color, and imaging device changes. Hence, we cannot fully depend on the raw color recorded by a camera. So, the assumption...

This paper presents a real-time processing platform for high-definition stereo video. The system is capable to process stereo video streams at resolutions up to 1, 920 × 1, 080 at 30 frames per second (1080p30). In the hybrid FPGA-GPU-CPU system, a high-density FPGA is used not only to perform the low-level image processing tasks such as color interpolation and cross-image color correction, but...

Previous work has shown that independent component analysis (ICA) applied to feature extraction from natural image data yields features resembling Gabor functions and simple-cell receptive fields. This article considers the effects of including chromatic and stereo information. The inclusion of colour leads to features divided into separate red/green, blue/yellow, and bright/dark channels. Ster...

Stereo vision is the most universal way to get 3D information passively. The fast progress of digital image processing hardware makes this computation approach realizable now. It is well known that stereo vision matches 2 or more images of a scene, taken by image sensors from different points of view. Any information loss, even partially in those images, will drastically reduce the precision an...

This paper presents a unified recognition and stereo vision system which locates objects and determines their distances and sizes given stereo video input. Unlike other such systems, the recognition stage precedes and provides input to stereo processing. Model-based recognition is accomplished in two stages. The first stage seeks feature matches by comparing the absolute orientation, relative o...