Abstract
Human visual system always focuses on the salient region of an image. From that region the salient features are obtained and can be collected by generating the saliency map. Natural statistics measures are used to measure the saliency from data collection of natural images. ICA filters are used to generate the saliency map that can blur the image. We have improved it by using different techniques like edge detection and morphological operations. By applying these algorithms we have successfully reduced the blur in images. That makes the salient objects more prominent by sharpening the edges. Proposed method is also compared with the state-of-the-art method like Achanta model.
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Yousaf, R.M. et al. (2017). Saliency Based Object Detection and Enhancements in Static Images. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_14
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DOI: https://doi.org/10.1007/978-981-10-4154-9_14
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