Heung-Kyu Lee

Inflammasome recognition of influenza virus is essential for adaptive immune responses

Influenza virus infection is recognized by the innate immune system through Toll like receptor (TLR) 7 and retinoic acid inducible gene I. These two recognition pathways lead to the activation of type I interferons and resistance to infection. In addition, TLR signals are required for the CD4 T cell and IgG2a, but not cytotoxic T lymphocyte, responses to influenza virus infection. In contrast, the role of NOD-like receptors (NLRs) in viral recognition and induction of adaptive immunity to influenza virus is unknown. We demonstrate that respiratory infection with influenza virus results in the activation of NLR inflammasomes in the lung. Although NLRP3 was required for inflammasome activation in certain cell types, CD4 and CD8 T cell responses, as well as mucosal IgA secretion and systemic IgG responses, required ASC and caspase-1 but not NLRP3. Consequently, ASC, caspase-1, and IL-1R, but not NLRP3, were required for protective immunity against flu challenge. Furthermore, we show that caspase-1 inflammasome activation in the hematopoietic, but not stromal, compartment was required to induce protective antiviral immunity. These results demonstrate that in addition to the TLR pathways, ASC inflammasomes play a central role in adaptive immunity to influenza virus.

Absence of autophagy results in reactive oxygen species-dependent amplification of RLR signaling

Autophagy is a highly conserved process that maintains homeostasis by clearing damaged organelles and long-lived proteins. The consequences of deficiency in autophagy manifest in a variety of pathological states including neurodegenerative diseases, inflammatory disorders, and cancer. Here, we studied the role of autophagy in the homeostatic regulation of innate antiviral defense. Single-stranded RNA viruses are recognized by the members of the RIG-I-like receptors (RLRs) in the cytosol. RLRs signal through IPS-1, resulting in the production of the key antiviral cytokines, type I IFNs. Autophagy-defective Atg5−/− cells exhibited enhanced RLR signaling, increased IFN secretion, and resistance to infection by vesicular stomatitis virus. In the absence of autophagy, cells accumulated dysfunctional mitochondria, as well as mitochondria-associated IPS-1. Reactive oxygen species (ROS) associated with the dysfunctional mitochondria were largely responsible for the enhanced RLR signaling in Atg5−/− cells, as antioxidant treatment blocked the excess RLR signaling. In addition, autophagy-independent increase in mitochondrial ROS by treatment of cells with rotenone was sufficient to amplify RLR signaling in WT cells. These data indicate that autophagy contributes to homeostatic regulation of innate antiviral defense through the clearance of dysfunctional mitochondria, and revealed that ROS associated with mitochondria play a key role in potentiating RLR signaling.

DE-Based Reversible Data Hiding With Improved Overflow Location Map

For difference-expansion (DE)-based reversible data hiding, the embedded bit-stream mainly consists of two parts: one part that conveys the secret message and the other part that contains embedding information, including the 2-D binary (overflow) location map and the header file. The first part is the payload while the second part is the auxiliary information package for blind detection. To increase embedding capacity, we have to make the size of the second part as small as possible. Tians classical DE method has a large auxiliary information package. Thodi mitigated the problem by using a payload-independent overflow location map. However, the compressibility of the overflow location map is still undesirable in some image types. In this paper, we focus on improving the overflow location map. We design a new embedding scheme that helps us construct an efficient payload-dependent overflow location map. Such an overflow location map has good compressibility. Our accurate capacity control capability also reduces unnecessary alteration to the image. Under the same image quality, the proposed algorithm often has larger embedding capacity. It performs well in different types of images, including those where other algorithms often have difficulty in acquiring good embedding capacity and high image quality.

Invariant image watermark using Zernike moments

The paper introduces a robust image watermark based on an invariant image feature vector. Normalized Zernike moments of an image are used as the vector. The watermark is generated by modifying the vector. The watermark signal is designed with Zernike moments. The signal is added to the cover image in the spatial domain after the reconstruction process. We extract the feature vector from the modified image and use it as the watermark. The watermark is detected by comparing the computed Zernike moments of the test image and the given watermark vector. Rotation invariance is achieved by taking the magnitude of the Zernike moments. An image normalization method is used for scale and translation invariance. The robustness of the proposed method is demonstrated and tested using Stirmark 3.1. The test results show that our watermark is robust with respect to geometrical distortions and compression.

Detection of copy-rotate-move forgery using Zernike moments

As forgeries have become popular, the importance of forgery detection is much increased. Copy-move forgery, one of the most commonly used methods, copies a part of the image and pastes it into another part of the the image. In this paper, we propose a detection method of copy-move forgery that localizes duplicated regions using Zernike moments. Since the magnitude of Zernike moments is algebraically invariant against rotation, the proposed method can detect a forged region even though it is rotated. Our scheme is also resilient to the intentional distortions such as additive white Gaussian noise, JPEG compression, and blurring. Experimental results demonstrate that the proposed scheme is appropriate to identify the forged region by copy-rotate-move forgery.

Reversible data hiding exploiting spatial correlation between sub-sampled images

Reversible data hiding enables host media to be restored from marked media without any loss of host information. Since this reversibility helps to make right decision during image analysis, it is highly desired in quality-sensitive imagery where even the minimal distortion introduced by embedding data is unacceptable. In this paper, we propose a reversible data hiding method that modifies the difference histogram between sub-sampled images. It exploits the high spatial correlation inherent in neighboring pixels to achieve high capacity and imperceptible embedding. On various test images including 16-bit images, we demonstrate the validity of our proposed method by comparing to other existing reversible data hiding algorithms. Experimental results support that our method provides high embedding capacity while keeping the distortions at a low level.

Robust image watermarking using local invariant features

This paper addresses a novel robust watermarking method for digital images using local invariant features. Most previous water- marking algorithms are unable to resist geometric distortions that desyn- chronize the location where copyright information is inserted. We pro- pose a watermarking method that is robust to geometric distortions. In order to resist geometric distortions, we use a local invariant feature of the image called the scale-invariant feature transform SIFT, which is invariant to translation and scaling distortions. The watermark is inserted into the circular patches generated by the SIFT. Rotation invariance is achieved using the translation property of the polar-mapped circular patches. Our method belongs to the blind watermark, because we do not need the original image during detection. We have performed an inten- sive simulation to show the robustness of the proposed method. The simulation results support the contention that our method is robust against geometric distortion attacks as well as signal-processing attacks. We have compared our results with those of other methods, and our method outperforms them.

Color Extended Visual Cryptography Using Error Diffusion

Color visual cryptography (VC) encrypts a color secret message into color halftone image shares. Previous methods in the literature show good results for black and white or gray scale VC schemes, however, they are not sufficient to be applied directly to color shares due to different color structures. Some methods for color visual cryptography are not satisfactory in terms of producing either meaningless shares or meaningful shares with low visual quality, leading to suspicion of encryption. This paper introduces the concept of visual information pixel (VIP) synchronization and error diffusion to attain a color visual cryptography encryption method that produces meaningful color shares with high visual quality. VIP synchronization retains the positions of pixels carrying visual information of original images throughout the color channels and error diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.

Robust DT-CWT Watermarking for DIBR 3D Images

The popularity of 3D content is on the rise since it provides an immersive experience to viewers. In this situation, depth-image-based rendering (DIBR) has taken on an important role in 3D technology due to its low bandwidth cost and ease of depth configuration. Noting that the viewer could record provided center view or synthesized views for illegal distribution, it is clear that copyright protection must be taken into account for the DIBR 3D content, including the possibility that one single view could be illegally distributed as 2D content. In this paper, we propose a robust watermarking scheme for DIBR 3D images by quantization on dual-tree complex wavelet transform (DT-CWT) coefficients with consideration of imperceptibility. To make the proposed scheme robust to DIBR process, two characteristics of DT-CWT are employed: approximate shift invariance and directional selectivity. We select certain coefficient sub-blocks and group the coefficient rows based on the properties of DIBR. On the extraction side, the threshold is carefully chosen with a low false positive rate. The simulation results show that the embedded watermark is stably extracted from the center view and the synthesized left and right views. In addition, even if the synthesized left and right views are distorted by general attacks, the watermark is successfully extracted. Furthermore, the proposed scheme is robust to pre-processing of the depth image and baseline adjusting, which are common processing on the DIBR system for better quality of 3D views.

Difference Expansion Based Reversible Data Hiding Using Two Embedding Directions

Current difference-expansion (DE) embedding techniques perform one layer embedding in a difference image. They do not turn to the next difference image for another layer embedding unless the current difference image has no expandable differences left. The obvious disadvantage of these techniques is that image quality may have been severely degraded even before the later layer embedding begins because the previous layer embedding has used up all expandable differences, including those with large magnitude. Based on integer Haar wavelet transform, we propose a new DE embedding algorithm, which utilizes the horizontal as well as vertical difference images for data hiding. We introduce a dynamical expandable difference search and selection mechanism. This mechanism gives even chances to small differences in two difference images and effectively avoids the situation that the largest differences in the first difference image are used up while there is almost no chance to embed in small differences of the second difference image. We also present an improved histogram-based difference selection and shifting scheme, which refines our algorithm and makes it resilient to different types of images. Compared with current algorithms, the proposed algorithm often has better embedding capacity versus image quality performance. The advantage of our algorithm is more obvious near the embedding rate of 0.5 bpp.