Dalian University of Technology

Dalian University

Rongrong Chen

Bin Wang

Xiaopeng Wei

Qiang Zhang

Pengfei Wang

Yuandi Shi

XiaoPeng Wei

Haixiao Li

Jun Tan

The present disclosure discloses a method for watermarking depth image based on mixed frequency-domain channel attention, relating to the field of artificial neural networks and digital image watermarking; the method includes: step 1: a watermark information processor generating a watermark information feature map; step 2: an encoder generating a watermarked image from a carrier image and a watermark information feature map; step 3: a noise layer taking the watermarked image as an input, and generating a noise image through simulated differentiable noise; step 4: a decoder down-sampling the noise image to recover watermark information; step 5: a countermeasure discriminator classifying the carrier image and the watermarked image such that the encoder generates a watermarked image with a high quality. The present disclosure combines the end-to-end depth watermark model with frequency-domain channel attention to expand an application range of the depth neural network in the field of image watermark.

Method for watermarking depth image based on mixed frequency-domain channel attention

The present disclosure discloses an image encryption method based on multi-scale compressed sensing and a Markov model. According to the difference in information carried by low-frequency coefficients and high-frequency coefficients of an image, different sampling rates are set for the low-frequency coefficients and the high-frequency coefficients of the image, which can effectively improve the reconstruction quality of a decrypted image. The decrypted image obtained by the present disclosure has higher quality than the decrypted image generated by the existing scheme, and a better visual effect and more complete original image information can be obtained.

Image encryption method based on multi-scale compressed sensing and Markov model

The present invention discloses an image encryption method based on an improved class boosting scheme, which comprises the following steps: acquiring parameters of a hyperchaotic system according to plaintext image information; generating weights required by class perceptron networks through the plain text image information; bringing the parameters into the hyperchaotic system to obtain chaotic sequences, and shuffling the chaotic sequences by a shuffling algorithm; pre-processing the chaotic sequences after shuffling to obtain a sequence required by encryption: and bringing a plaintext image and the sequence into an improved class boosting scheme to obtain a ciphertext image, wherein the improved class boosting scheme is realized based on the class perception networks. The method solves the problems that update and prediction functions in an original boosting network are too simple and easy to predict or the like, so as to obtain the ciphertext image with higher information entropy.

Image encryption method based on improved class boosting scheme

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Dalian, China

Rongrong Chen