A Novel Method for Calculating Depth Distortion Scores in 3-D Image Retargeting

Abstract

3D Image quality degradation can be observed by measuring the depth distortion of an image. The depth distortion is based on the adjustment of image aspect ratio. This aspect ratio can be increased in order to achieve the better depth, which subsequently reduces the degradation in the 3D image. This phenomenon is applied on 3D animated movies by abolishing the blurriness in the pair of images. These pair of images are called as ‘stereo images. The stereo images are found in the pairs such as left stereo image and right stereo image.  In 3D animated movies, different viewpoints are designed for left and right eye. So, when anyone observes the movie with naked eyes, the accuracy in visibility get affected. This problem can be eradicated by wearing the chemically affected 3D sterilize goggles for a short span of time.  The proposed method of The Disparity Map Acquisition (DMA) can achieve the task in some significant way, which gives rise to the depth distortion with improved disparity matrix. In this paper, we emphasis on depth score enhancement in 3D stereo images retargeting to accomplish the acceptable 3D images with improved depth distortion score. The experimental results show the stereo seam carving that neglects the unwanted image patches in order to generate an acceptable 3D stereo image. with the better visual effects. This may lead to the non-usability of 3D sterilize goggles and eventually helps and reduces the burden on Indian economy.