This paper proposes a method of embedding and extracting watermark in end-to-end (E2E) image compression that is an emerging image compression framework. Although end-to-end image compression algorithms are recently developed based on deep neural networks to beat the conventional image compression methods, there are no research to support watermarking embedment and extraction for contents protections. This paper proposes a NN-based watermarking algorithm for end-to-end image coding. At the end-to-end image coder and decoder, the GDN-based multi-layer modules for embedment and extraction of watermark are equipped to support watermarking for E2E image compressor. The proposed method shows an average BD-rate gain of 8.07%, over the method of directly connecting the existing watermarking network and end-to-end image compression network. In addition, bit error rate (BER) of watermark is also improved by more than 2.7% in terms of robustness.
Digital Hologram is a very high-value-added image content, whose intellectual property should be protected for its distribution. Therefore its watermarking technology has become much important. This paper is to propose a training scheme of a deep neural network to perform a digital watermarking for a digital hologram. We construct various training datasets according to the distribution of holograms and train them on the proposed network. The network consists of preprocessing networks for both host data and watermark, watermark embedding network, and watermark extraction network, all of which consist of simple convolutional neural network (CNN) modules. The dataset is constructed with the digital holograms from JPEG Pleno and they are classified by distribution of the hologram pixel values. The network is trained with each of the classified holograms. With each of the trained weight sets, the invisibility and watermark extraction rate are calculated and compared with the results from testing the test dataset that has not been used for training. From the result, we explain the effects of the data distribution of the training dataset on the invisibility and robustness of the watermarking to present the best training scheme for a digital watermarking of a digital hologram.
KEYWORDS: Digital watermarking, Digital holography, Holograms, 3D image reconstruction, Near field diffraction, Optical engineering, Wave propagation, Light wave propagation, Computer generated holography, Diffraction
Since holograms are very costly content, security against holograms is very important. Hologram watermarking has been researched for a long time as a security solution for the digital hologram distributed on the network as the hologram is digitized. We deal with a digital watermarking for digital hologram contents as ownership protection tool. Since holograms have different optical characteristics from natural images, a watermarking technique using these characteristics should be needed. We therefore selected Fresnel diffraction for this property. Both of the host holograms and the watermarks are diffracted more than once for each. The results are refracted to concentrate the diffracted data into the localized regions of the transformed plane so that the region occupied one region among them. From this process, we change and select the region of the watermark. We experimented our scheme with various test images for various attacks on data-manipulating attack and geometric attack. It is apparently recognizable for eye inspection. From the results, we expect the proposed watermarking scheme to be an appropriate solution for protecting the ownership of holograms.
We propose a new system that can generate digital holograms using natural color information. The system consists of a camera system for capturing images (object points) and software (S/W) for various image processing. The camera system uses a vertical rig, which is equipped with two depth and RGB cameras and a cold mirror, which has different reflectances according to wavelength for obtaining images with the same viewpoint. The S/W is composed of the engines for processing the captured images and executing computer-generated hologram for generating digital holograms using general-purpose graphics processing units. Each algorithm was implemented using C/C++ and CUDA languages, and all engines in the form of library were integrated in LabView environment. The proposed system can generate about 10 digital holographic frames per second using about 6 K object points.
KEYWORDS: Digital holography, Holograms, Video coding, Video, Image segmentation, Video compression, 3D video compression, 3D scanning, 3D image reconstruction, Fringe analysis
In this paper, we proposed a new coding technique of digital hologram video using 3D scanning method and video compression technique. The proposed coding consists of capturing a digital hologram to separate into RGB color space components, localization by segmenting the fringe pattern, frequency transform using M×N (segment size) 2D DCT (2 Dimensional Discrete Cosine Transform) for extracting redundancy, 3D scan of segment to form a video sequence, motion compensated temporal filtering (MCTF) and modified video coding which uses H.264/AVC. The compressed digital hologram was reconstructed by both computer program and optic system. The proposed algorithm showed better properties after reconstruction with higher compression ratios than the previous researches.
KEYWORDS: Image compression, Digital holography, Image segmentation, Holograms, Fringe analysis, 3D image reconstruction, Holography, Video, Video coding, Digital imaging
We propose an efficient coding method of digital holograms (or fringe patterns) using standard compression tools for video and image. The fringe pattern is generated by a computer-generated hologram (CGH) algorithm with both an object image and its depth information. The proposed coding consists of preprocessing to separate RGB color space components, localization by segmenting the fringe pattern, frequency transform using M×N (segment size), 2-D discrete cosine transform (DCT) for extracting redundancy, segment scanning the segmented fringe pattern to form a video sequence, classification of coefficients, and hybrid video coding, which uses MPEG-2/4, H.264/AVC, differential pulse code modulation (DPCM), and lossless coding. The proposed algorithm illustrates that it has better properties for reconstruction, from four to eight times higher compression rate than previous research.
JPEG2000 was established as an international standard for still image compression by ISO/IEC/ITU-T. This paper
proposed a method to perform network adaptive context extraction with high speed, which takes the largest portion in
calculation of EBCOT. This algorithm is to extract the context for coefficients whose value is more than or equal to a
transfer factor about the network environment. The speed and network-adaptive power is up at the cost of degrading the
image quality about transfer factor. The transfer factor was from 20 to 1 with the image quality of between 50dB and
30dB, at which from 20% to 60% of the amount of calculation and data was reduced. Since the degradation in image
quality can be adjusted by the transmission factor, the proposed method is expected to be used effectively in conjunction
with the progressive transmission methods according to the image quality. Also by implementing hardware IP, it is
expected to be able to be used in designing a JPEG2000 system.
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