Image Stitching

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Abstract-: Image Stitching or mosaicing is an important aspect of research in the field of computer vision. It involves various techniques of joining images together to form a mosaic of high resolution. Stitching images generally require complete overlap in order to generate high resolution panoramas. As these panoramas become increasingly popular, there arises a need for the software to create mosaics. These mosaics are used for variety of applications like in digital maps and satellite photos. In recent years various techniques have been generated to do stitching in order to obtain data from images. Such techniques which have been used to successfully combine images are discussed in this paper.

Keywords: Image Stitching, Panorama, Feature
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Typical flow diagram of Image Stitching

These processes play an important role in stitching of images. Once the feature sets are computed, the images need to be stitched together along the overlapping regions using a blending algorithm. Prior to blending, alignment is necessary. Alignment minimizes the miss-registration that removes double edges and blurring. Now the aligned images are stitched together using a blending algorithm. Blending can be done by projecting images onto some composition surface like cylindrical, planer, fisheye etc. This paper is organized as follows: in section 2, we present main steps required for image stitching. Furthermore, section 3 presents a detailed summary on approaches to tackle image stitching. In section 4 we present the discussion on various approaches to image mosaicing and in section 5, future of image stitching is discussed.

Fig2. From left to right (a) Input image 1 (b) Input image 2

Fig3. Various blending composition surfaces on which the aligned images are projected
(a) cylindrical (b) spherical (c) fisheye (d) stereographical ( panini
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Haar wavelet technique discussed above uses gradient method which provides solution to local adjustments in image by making it an optimization problem. Energy factor could also be taken to optimize the process. This type of mosaic development from Haar wavelet can be enhanced so that complex images can be combined easily in future. Other techniques are also there which provide seamless stitching of images. For summary, it would suffice that various techniques of stitching like gradient-based, optical seam, Harris corner method etc. have evolved the enhancement of pictures making them used extensively in today’s research and

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