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Binary images have only two distinct pixel color values so the capability of data hiding is very limited. To improve the robustness of watermarking algorithm, we proposed a novel ridgelet based watermarking for binary images. Ridgelet transform is efficient for representing images with line singularities. So, binary host image is partitioned into several non-overlapping blocks to make edges in each...
In this paper, a local watermarking scheme in the ridgelet domain combining image content and JND model is presented. Since the ridgelet transform (RT) can efficiently represent image with linear singularities and has directional sensitivity, the image is partitioned into small pieces. And these small pieces are classified into different characteristic categories (S1 with weak texture, S2 with strong...
A novel robust watermark embedding and extracting algorithm in ridgelet domain is proposed. Since the ridgelet transform (RT) can efficiently represent image with linear singularities and has directional sensitivity, the image is first partitioned into small pieces. Firstly these small pieces are classified to different characteristic categories (with weak texture, strong texture) according to the...
An adaptive blind watermarking algorithm based on image content and ridgelet transform is proposed. Firstly, the image is divided into three different feature regions: smooth, edge and texture. And then, due to the sparse representation of ridgelet transform for image features, the positions of important vision information where watermark should be embedded can be found out. The watermark is embedded...
Image Compression is a widely addressed research area. Many compression standards are in place. There are many methods for image classification. But the joint compression and classification is a new research area wherein the classification is attempted in the compressed domain. The joint compression and classification (JCC) is explored in wavelet domain by some researchers. But it is not yet explored...
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