Fast and High-Quality Image Blending on Mobile Phones

Abstract

We present a fast and high-quality image stitching approach for creating high-resolution and high-quality panoramic images on mobile devices. In the approach, a sequential panorama stitching procedure is created with color and luminance compensation for reducing differences between source images, fast image labeling for optimal seam finding, and gradient domain image blending for transition smoothing. The color and luminance compensation is performed in the gamma-corrected sRGB color space to avoid pixel saturation problems, optimal seams between adjacent source images are found by dynamic programming optimization for fast speed and less memory, and the source images are blended together by Poisson blending for a high blending quality. We compare results and performance with other approaches to demonstrate the advantages of our approach in mobile panorama applications. The main contribution of this work is studying how applying color and luminance compensation before Poisson blending improves the blending quality and processing speed of Poisson blending in long image sequences where colors and luminance vary between source images, and how it also improves the quality of image labeling. The integration of color correction, fast labeling, and Poisson blending into a sequential panorama stitching procedure allows creation of high-resolution panoramic images with large source images more quickly and using less memory. These are very important aspects for mobile devices that have limited computational power and memory resources.