Very fast watermarking by reversible contrast mapping

Reversible contrast mapping (RCM) is a simple integer transform that applies to pairs of pixels. For some pairs of pixels, RCM is invertible, even if the least significant bits (LSBs) of the transformed pixels are lost. The data space occupied by the LSBs is suitable for data hiding. The embedded information bit-rates of the proposed spatial domain reversible watermarking scheme are close to the highest bit-rates reported so far. The scheme does not need additional data compression, and, in terms of mathematical complexity, it appears to be the lowest complexity one proposed up to now. A very fast lookup table implementation is proposed. Robustness against cropping can be ensured as well

Exact Histogram Specification Optimized for Structural Similarity

An exact histogram specification (EHS) method modifies its input image to have a specified histogram. Applications of EHS include image (contrast) enhancement (e.g., by histogram equalization) and histogram watermarking. Performing EHS on an image, however, reduces its visual quality. Starting from the output of a generic EHS method, we maximize the structural similarity index (SSIM) between the original image (before EHS) and the result of EHS iteratively. Essential in this process is the computationally simple and accurate formula we derive for SSIM gradient. As it is based on gradient ascent, the proposed EHS always converges. Experimental results confirm that while obtaining the histogram exactly as specified, the proposed method invariably outperforms the existing methods in terms of visual quality of the result. The computational complexity of the proposed method is shown to be of the same order as that of the existing methods. Index terms: histogram modification, histogram equalization, optimization for perceptual visual quality, structural similarity gradient ascent, histogram watermarking, contrast enhancement

Depth Estimation and Image Restoration by Deep Learning from Defocused Images

Monocular depth estimation and image deblurring are two fundamental tasks in computer vision, given their crucial role in understanding 3D scenes. Performing any of them by relying on a single image is an ill-posed problem. The recent advances in the field of Deep Convolutional Neural Networks (DNNs) have revolutionized many tasks in computer vision, including depth estimation and image deblurring. When it comes to using defocused images, the depth estimation and the recovery of the All-in-Focus (Aif) image become related problems due to defocus physics. Despite this, most of the existing models treat them separately. There are, however, recent models that solve these problems simultaneously by concatenating two networks in a sequence to first estimate the depth or defocus map and then reconstruct the focused image based on it. We propose a DNN that solves the depth estimation and image deblurring in parallel. Our Two-headed Depth Estimation and Deblurring Network (2HDED:NET) extends a conventional Depth from Defocus (DFD) networks with a deblurring branch that shares the same encoder as the depth branch. The proposed method has been successfully tested on two benchmarks, one for indoor and the other for outdoor scenes: NYU-v2 and Make3D. Extensive experiments with 2HDED:NET on these benchmarks have demonstrated superior or close performances to those of the state-of-the-art models for depth estimation and image deblurring

Morphological evaluation of the different methods used for protection of colonic anastomosis

First Department of Surgery “N. Anestiadi” and Laboratory of Hepato-Pancreato-Biliary Surgery, Medical University "N.Testemitanu", Chisinau , RMIntroduction: Despite the performances of modern medicine, especially of colorectal surgery, anastomotic leakage remains one of the most dangerous postoperative complications, without significant trend of decreasing. Morbidity and mortality increase considerably after the development of an anastomotic leakage. Anastomotic leakage presents an important problem of public health with major socio-economic impact and can be considered one of the quality indicators of specialized surgical centers' activity. There are multiple studies running in order to create and assess the efficacy of colonic anastomosis local protection methods. Aim of study was morphological evaluation of the methods used for local protection of anastomotic zone and their influence on the anastomosis healing. Materials and methods: Sixty three rats were divided in three groups: colonic anastomosis was performed and topical latex tissue adhesive was applied in the group I (n=21); colonic anastomosis with local application of collagen patch in the group II; colonic anastomosis without local protection in the group III. Results: Anastomotic leakage was not determined in the group I vs the group III, where were detected 5 cases of anastomotic leakage. According to the present study’s data in the group I was determined early diminution exudativ-detersiv process’ activity vs groups II and III (p<0.01). Latex tissue adhesive has positive influence on the processes of neoangiogenesis and fibrilogenesis in the anastomotic zone on the 14th POD vs the group II and III (p<0.05). According to ours data latex tissue adhesive has considerable compatibility with colonic tissue that represents the absence of giant like „foreign bodies” symplasts and insignificant immunologic reaction of large bowel. Aggressive bacterial colonization in this group has contributed for appearance of anastomotic leakage, formation of abscesses and granulomatous processes like „foreign bodies”. Mentioned processes considerable have complicated synchronous evolution of neoangiogenesis and fibrilogenesis in the anastomotic zone, resulted in decreasing of the primary healing, appearance of anastomotic deformations and expression of the adhesion process vs anastomosis from the groups I and III. Conclusion: Using of latex tissue adhesive for local protection of colonic anastomosis improves anastomotic healing, processes of neoangiogenesis and fibrilogenesis. Using of collagen patch for local protection of colonic anastomosis doesn’t have any advantages and provokes delaying of regeneratory processes and persisting of an inflammatory process

Computing negentropy based signatures for texture recognition

The proposed method aims to provide a new tool for texture recognition. For this purpose, a set of texture samples are decomposed by using the FastICA algorithm and characterized by a negentropy based signature. In order to do recognition, the texture signatures are compared by means of Minkowski distance. The recognition rates, computed for a set of 320 texture samples, show a medium recognition accuracy and the method may be further improved

Traumatic Diaphragmatic Rupture (Review)

Leziunile traumatice ale diafragmei sunt potenţial fatale şi prezintă difi cultăţi diagnostice. Implicarea diafragmei este relativ rară (5-7%), factorul etiologic dominant fiind traumatismele închise şi penetrante toracice şi abdominale. La momentul actual nici una din metodele de investigare nu asigură stabilirea diagnosticului cert de leziune traumatică a diafragmei în timpul spitalizării primare a pacientului. Radiografi a toracoabdominală este considerată informativă în circa 33% din cazuri, totuşi informativitatea este redusă în cazul pacienţilor intubaţi. Deşi leziunea traumatică a diafragmei nu este una letală, mortalitatea şi morbiditatea semnifi cative sunt condiţionate de leziunile concomitente vasculare şi viscerale, precum şi diagnosticării incorecte. În acest context diagnosticarea precoce este obligatorie deoarece cazurile nediagnosticate sunt asociate cu rate semnifi cative de morbiditate şi mortalitate

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

This work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique ‘IRW-Med’, the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset

On the Use of Normalized Compression Distances for Image Similarity Detection

his paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection. Instead of the direct NCD between images, the paper considers the correlation between NCD based feature vectors extracted for each image. The vectors are derived by computing the NCD between the original image and sequences of translated (rotated) versions. Feature vectors for simple transforms (circular translations on horizontal, vertical, diagonal directions and rotations around image center) and several standard compressors are generated and tested in a very simple experiment of similarity detection between the original image and two filtered versions (median and moving average). The promising vector configurations (geometric transform, lossless compressor) are further tested for similarity detection on the 24 images of the Kodak set subject to some common image processing. While the direct computation of NCD fails to detect image similarity even in the case of simple median and moving average filtering in 3 × 3 windows, for certain transforms and compressors, the proposed approach appears to provide robustness at similarity detection against smoothing, lossy compression, contrast enhancement, noise addition and some robustness against geometrical transforms (scaling, cropping and rotation