Holoentropy measures for image stitching of scenes acquired under CAMERA unknown or arbitrary positions

Image stitching of similar scenes is a challenging task when scenes are captured under varying illuminations between the scenes, varying camera positions, varying orientations either in axial or azimuth. In this paper, we explore a seamless image stitching algorithm to address the above-said issues by applying techniques of dehazing on the acquired scenes and before identifying the image features and holoentropy aided feature matching on the Scale Invariant Feature Transform (SIFT) based features for the image. Experimentation of the proposed system is compared with the existing image stitching methods using squared distance, Minkowski and pairwise Euclidean distance for feature matching. The proposed seamless stitching method is evaluated based on the metrics, horizontal square gradient value (HSGV) and vertical square gradient value (VSGV). The obtained results are shown to be feasible for stitching the nonuniform or illumination variation multiple images. The exploration of above said stitching algorithm is intended to reduce the number of computations and inconsistencies in the stitched results.