Automatic Shadow Detection and Removal from a Single Image

Abstract

We present a framework to automatically detect and remove shadows in real world scenes from a single image. Previous works on shadow detection put a lot of effort in designing shadow variant and invariant hand-crafted features. In contrast, our framework automatically learns the most relevant features in a supervised manner using multiple convolutional deep neural networks (ConvNets). The features are learned at the super-pixel level and along the dominant boundaries in the image. The predicted posteriors based on the learned features are fed to a conditional random field model to generate smooth shadow masks. Using the detected shadow masks, we propose a Bayesian formulation to accurately extract shadow matte and subsequently remove shadows. The Bayesian formulation is based on a novel model which accurately models the shadow generation process in the umbra and penumbra regions. The model parameters are efficiently estimated using an iterative optimization procedure. Our proposed framework consistently performed better than the state-of-the-art on all major shadow databases collected under a variety of conditions.

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

“…The current methods for shadow detection can be divided into three types [11][12][13]: (1) property-based methods [9,[13][14][15][16][17][18][19][20]; (2) geometrical methods [14,[17][18][19][20]; and (3) machine learning methods [15,16,21,22].…”

Analysis on Removal of Vehicle Shadow Based on Edge Feature and HSV Color Space

“…Several works have proposed detection and removal algorithms based on shadow models and feature characterization [4][5][6][7][8][9]. Theoretical studies and practical applications of these algorithms play an important role in the development of intelligent transportation systems.…”

Development of an Improved Algorithm for Image Processing: A Proposed Algorithm for Optimal Reduction of Shadow from the Image

“…In the case of colour images, it may differ subjected to the type of platform that is being used to render the image. A study by [7] presented a framework to automatically detect and remove shadows in natural scenes from a single image. A lot of efforts are made in designing invariant hand-crafted and shadow variant features.…”