Ratio-Preserving Half-Cylindrical Warps for Natural Image Stitching
This work addresses image distortion issues in stitching for applications like photography and computer vision, but it is incremental as it builds on existing warp techniques.
The paper tackles projective distortion in natural image stitching by proposing a ratio-preserving half-cylindrical warp that combines homography and cylindrical warps, along with a horizontal pixel selection strategy, resulting in more natural-looking stitched images compared to previous methods.
A novel warp for natural image stitching is proposed that utilizes the property of cylindrical warp and a horizontal pixel selection strategy. The proposed ratio-preserving half-cylindrical warp is a combination of homography and cylindrical warps which guarantees alignment by homography and possesses less projective distortion by cylindrical warp. Unlike previous approaches applying cylindrical warp before homography, we use partition lines to divide the image into different parts and apply homography in the overlapping region while a composition of homography and cylindrical warps in the non-overlapping region. The pixel selection strategy then samples the points in horizontal and reconstructs the image via interpolation to further reduce horizontal distortion by maintaining the ratio as similarity. With applying half-cylindrical warp and horizontal pixel selection, the projective distortion in vertical and horizontal is mitigated simultaneously. Experiments show that our warp is efficient and produces a more natural-looking stitched result than previous methods.