A copyright protection watermarking algorithm for remote sensing image based on binary image watermark

Optik ◽  
2013 ◽  
Vol 124 (20) ◽  
pp. 4177-4181 ◽  
Author(s):  
Peng Zhu ◽  
Fei Jia ◽  
Junliang Zhang
2012 ◽  
Vol 433-440 ◽  
pp. 2504-2508 ◽  
Author(s):  
Li Li Li ◽  
Jin Guang Sun

In this paper it proposes a meaningful digital watermarking algorithm for remote sensing image based on DFT and watermarking segmentation. At First, it normalizes the host remote sensing image and determines an invariant centroid, then selects a square area around the invariant centroid for watermark embedding. Next, it generates a pseudo-random sequence as digital watermarking, and divides it into two parts. Finally it applies DFT to the selected region and embeds watermark into DFT phase and amplitude components of the selected square area of the host remote sensing image. Experiments have shown the algorithm’s characteristics of good robustness, simple calculation, easy realization, and extracting watermark without the original remote sensing image, and it has value of copyright protection for remote sensing images.


Author(s):  
Sumit Kaur

Abstract- Deep learning is an emerging research area in machine learning and pattern recognition field which has been presented with the goal of drawing Machine Learning nearer to one of its unique objectives, Artificial Intelligence. It tries to mimic the human brain, which is capable of processing and learning from the complex input data and solving different kinds of complicated tasks well. Deep learning (DL) basically based on a set of supervised and unsupervised algorithms that attempt to model higher level abstractions in data and make it self-learning for hierarchical representation for classification. In the recent years, it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. This paper will present a survey on different deep learning techniques for remote sensing image classification. 


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