Salient Building Outline Enhancement and Extraction Using Iterative L0 Smoothing and Line Enhancing
This work addresses the domain-specific problem of building outline extraction for applications like urban planning or mapping, but it appears incremental as it builds on existing L0 smoothing and line detection techniques.
The paper tackles the problem of enhancing and extracting salient building outlines from consumer camera images by addressing weak outlines and over-smoothing, proposing an iterative method with smoothing and sharpening cells that uses L0 smoothing and Hough Transform, and includes building masks from semantic segmentation and an evaluation dataset.
In this paper, our goal is salient building outline enhancement and extraction from images taken from consumer cameras using L0 smoothing. We address weak outlines and over-smoothing problem. Weak outlines are often undetected by edge extractors or easily smoothed out. We propose an iterative method, including the smoothing cell and sharpening cell. In the smoothing cell, we iteratively enlarge the smoothing level of the L0 smoothing. In the sharpening cell, we use Hough Transform to extract lines, based on the assumption that salient outlines for buildings are usually straight, and enhance those extracted lines. Our goal is to enhance line structures and do the L0 smoothing simultaneously. Also, we propose to create building masks from semantic segmentation using an encoder-decoder network. The masks filter out irrelevant edges. We also provide an evaluation dataset on this task.