The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA). The proposed method performance is evaluated in terms of PSNR, RMSE and SSIM. The results show that the fusion quality of the proposed algorithm is better than obtained by several other fusion methods, including SWT, PCA with RGB source images and PCA with YCbCr source images.
Comparison is the most common and effective technique for human thinking: the human mind always judges something new based on its comparison with similar things that are already known. Therefore, literary comparisons are always clear and convincing. In our daily lives, we are constantly forced to compare different things in terms of quantity, quality, or other aspects. It is known that comparisons are used in literature in order for speech to be clear and effective, but when these comparisons are used in everyday speech, it is in order to convey the meaning directly and quickly, because many of these expressions used daily are comparisons. In our research, we discussed this comparison as a means of metaphor and expression in Russia
... Show MoreIn this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-
... Show MoreIn the reverse engineering approach, a massive amount of point data is gathered together during data acquisition and this leads to larger file sizes and longer information data handling time. In addition, fitting of surfaces of these data point is time-consuming and demands particular skills. In the present work a method for getting the control points of any profile has been presented. Where, many process for an image modification was explained using Solid Work program, and a parametric equation of the profile that proposed has been derived using Bezier technique with the control points that adopted. Finally, the proposed profile was machined using 3-aixs CNC milling machine and a compression in dimensions process has been occurred betwe
... Show MoreGroupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff
... Show MoreThe computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.
Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,
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