In machine vision applications, distance or depth is an important factor. This paper describes stereoscopic depth calculation method by using images by two identical cameras separated by a small distance. This method requires calibration of cameras and rectification, an important step which is required for the matching of the images captured by two cameras. Using this stereo matching technique disparity is calculated. This is directly related to the depth. The proposed method is very much useful for planetary vision, autopilots, etc.

In this paper, an undecimated double density dual tree discrete wavelet transform (UDDDT-DWT) based image resolution enhancement technique is proposed. The critically sampled discrete wavelet transform (DWT) suffers from the drawbacks of being shift-variant and lacking the capacity to process directional information in images. The double density dual tree wavelet transform (DDDT-WT) is an approximately shift-invariant transform capturing directional information. The UDDDT-DWT is an improvement of the DDDT-DWT, making it exactly shift-invariant. The method uses a forward and inverse (UDDDT-DWT) to construct a high-resolution (HR) image from the given lower-resolution (LR) image. The HR image is reconstructed from the LR image using the inverse UDDDT-DWT. Results are presented and discussed through comparisons between state-of-the-art resolution enhancement methods.

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