Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method
Omkar S. Vaidya1, Sanjay T. Gandhe2
1Omkar S. Vaidya*, Department of Electronics and Telecommunication Engineering, Sandip Institute of Technology & Research Centre, Nashik, Affiliated to Savitribai Phule Pune University, Pune, India.
2Sanjay T. Gandhe, Department of Electronics and Telecommunication Engineering, Sandip Institute of Technology & Research Centre, Nashik, Affiliated to Savitribai Phule Pune University, Pune, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 10, 2020. | PP: 1494-1500 | Volume-9 Issue-5, March 2020. | Retrieval Number: E3011039520/2020©BEIESP | DOI: 10.35940/ijitee.E3011.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image Stitching is becoming more popular in field of computer vision because of rapid development of efficient algorithms that replaces the high cost wider lens cameras and commercial image stitching tools. The existing methods used global geometric transformation in registration stage and hence suffered from object deformation, parallax error, ghosting effect and motion blur in output result. In this paper, newly developed Hybrid Warping of weighted linearized homography matrix and similarity transform matrix is implemented over standard image stitching database. The visual quality of stitched image using proposed method has been examined in terms of performance metrics of Full Reference Image Quality Assessment (FRIQA) such as Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Reduced Reference Image Quality Assessment (RRIQA). Also, the performance analysis of proposed method is compared against existing image stitching methods in terms of field of view and stitching time. This analysis has ascertained the outperformance of Novel Hybrid Image Stitching method.
Keywords: Full Reference and Reduced Reference Image Quality Assessment, Homography, Hybrid Warping, Image Stitching, Panoramic View.
Scope of the Article: Image Processing and Pattern Recognition