Abstract
Predicting a pixel value in an image with the help of neighborhood pixels is important for several tasks, like image compression, reversible data hiding. The paper proposes a novel approach to predict the pixel intensities in an image using a multilayer perceptron. Experimental results show that the proposed method is more efficient than several popular pixel prediction methods.
Keywords
- Pixel Prediction
- Multilayer Perceptron (MLP)
- Gradient Adjusted Predictor (GAP)
- Neighboring Pixel Intensities
- Median Edge Detector (MED)
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Prabhakaran, A., Pal, R. (2019). Image Pixel Prediction from Neighborhood Pixels Using Multilayer Perceptron. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_17
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DOI: https://doi.org/10.1007/978-981-13-1595-4_17
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