Abstract
Color edge detection is preferred to grayscale edge detection because edges existing at the boundary separating regions of different textures which cannot be detected (in case of grayscale images) if there are no intensity changes. This paper proposes an approach for performance improvement of Hilbert transform based edge detector making it capable of color edge detection in noisy environment. Combining Bilateral filtering with Hilbert Transform produces good results in case of images contaminated with Gaussian and impulse noises. The initiation of the proposed edge detection approach is marked by the transformation of the input color image using RGB color triangle. Computer simulations are performed on noise free images as well as those corrupted with a mixture of Gaussian and impulse noises. Simulation results along with their quality assessment illustrate the effectiveness of the proposed approach in noise free as well as noisy environment.
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Gupta, A., Ganguly, A., Bhateja, V. (2013). An Edge Detection Approach for Images Contaminated with Gaussian and Impulse Noises. In: S, M., Kumar, S. (eds) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 222. Springer, India. https://doi.org/10.1007/978-81-322-1000-9_49
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DOI: https://doi.org/10.1007/978-81-322-1000-9_49
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