A Photograph Reconstruction Method Based on Parameter-Free Spectral Matting for Better Composition

Abstract

In digital photography, composition rules are essential for capturing highly aesthetic photographs. Aesthetic images create a response of visual appreciation to the viewers. Rule of thirds (RoT) is the most important and basic rule accepted by photographers for taking aesthetically pleasing shots. The important object is placed along the thirds-lines or intersections of thirds lines. In many cases, the aesthetic quality of the photograph taken from a traditional camera is improved if the photograph is produced to respects the rule of thirds. In this thesis, a novel computational approach, "Retarget Object for Implementation of Rule-of-Thirds'', (ROI-RT) is presented. The technique automatically improves the composition of photographs to follow the composition rule, rule-of-thirds (RoT). For achieving the said task, the main adopted steps are background-foreground estimation, main object segmentation, features extraction, background best patch detection, texture synthesis for occluded background, and retargeting the main object on synthesized background to reproduce a photograph which respect composition rule RoT, in photography. Experimental results show an overall acceptable performance of 94.30% for our method. A comparison with existing techniques shows that ROI-RT performs better in terms of visually aesthetic photographs.