Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Quantum color image scaling based on bilinear interpolation

As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images, with relatively little processing for color images. This paper proposes a quantum color image scaling scheme based on bilinear interpolation, which realizes the 2^(n_(1)) × 2^(n_(2)) quantum color image scaling. Firstly, the improved novel quantum representation of color digital images(INCQI) is employed to represent a 2^(n_(1)) × 2^(n_(2)) quantum color image, and the bilinear interpolation method for calculating pixel values of the interpolated image is presented. Then the quantum color image scaling-up and scaling-down circuits are designed by utilizing a series of quantum modules, and the complexity of the circuits is analyzed.Finally, the experimental simulation results of MATLAB based on the classical computer are given. The ultimate results demonstrate that the complexities of the scaling-up and scaling-down schemes are quadratic and linear, respectively, which are much lower than the cubic function and exponential function of other bilinear interpolation schemes.

Quantum Color Image Scaling on QIRHSI Model

Scaling operations are widely used in traditional image processing.Therefore, in this paper, an improved quantum image representation based on HSIcolor space (IQIRHSI) is proposed, which extends the original 2n × 2n size togeneral 2n1 × 2n2 size. Then, the quantum algorithms and circuits were designedto implement quantum image scaling. Interpolation was introduced to recover thelost information in the scaled image. The nearest neighbor interpolation methodwas researched on scaled IQIRHSI to make the interpolation method easy toimplement. Finally, the complexity of the quantum circuit for image scaling wasanalyzed and the process of quantum image scaling was described in detail byexamples.

Image matching algorithm based on SIFT using color and exposure information

Image matching based on scale invariant feature transform（SIFT） is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT.

A Secure Robust Gray Scale Image Steganography Using Image Segmentation

Steganography is the art of hiding a secret message in some kind of media. The main goal is not to hide only the secret message but also the existence of communication and secure data transferring. There are a lot of methods that were utilized for building the steganography;such as LSB (Least Significant Bits), Discrete Cosine Transform (DCT), Discrete Fourier Transform, Spread-Spectrum Encoding, and Perceptual Masking, but all of them are challenged by steganalysis. This paper proposes a new technique for Gray Scale Image Steganography that uses the idea of image segmentation and LSB to deal with such problem. The proposed method deals with different types of images by converting them to a virtual gray scale 24 bitmaps, finds out the possible segments inside image and then computes the possible areas for each segment with boundaries. Any intruder trying to find the transformed image will not be able to understand it without the correct knowledge about the transformation process. The knowledge is represented by the key of image segmentation, key of data distribution inside segment (area selection), key of mapping within each area segment, key agreement of cryptography method, key of secret message length and key of message extension. Our method is distinguishing oneself by one master key to generate the area selection key, pixels selection keys and cryptography key. Thus, the existence of secret message is hard to be detected by the steganalysis. Experiment results show that the proposed technique satisfied the main requirements of steganography;visual appearance, modification rate, capacity, undetectability, and robustness against extraction (security). Also it achieved the maximum capacity of cover image with a modification rate equals 0.04 and visual quality for stego-image comparable to cover image.

Design on AM-OLED display control ASIC with high gray scale levels

The paper puts forward a method on controlling the AM-OLED panel to display image with high gray scale levels. It also gives an ASIC design sample to implement this method. A twenty sub-fields scan scheme has been taken into use in the chip to display 256 gray scale levels on a QVGA resolution AM-OLED display screen. The functions of image scaling and rotating have also been implemented for multiply application. The simulation and chip test result show that the chip design has met the design requirements.

Rotational parameters estimation of maneuvering target in ISAR imaging

The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.

Design and Implementation of Verification Code Identification Based on Anisotropic Heat Kernel

Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.

3D Urban Visualization with LOD Techniques

In 3D urban visualization, large data volumes related to buildings are a major factor that limits the delivery and browsing speed in a web-based computer system. This paper proposes a new approach based on the level of detail （LOD） technique advanced in 3D visualization in computer graphics. The key idea of LOD technique is to generalize details of object surfaces without losing details for delivery and displaying objects. This technique has been successfully used in visualizing one or a few multiple objects in films and other industries. However, applying the technique to 3D urban visualization requires an effective generalization method for urban buildings. Conventional two-dimensional （2D） generalization method at different scales provides a good generalization reference for 3D urban visualization, Yet, it is difficult to determine when and where to retrieve data for displaying buildings. To solve this problem, this paper defines an imaging scale point and image scale region for judging when and where to get the fight data for visualization. The results show that the average response time of view transformations is much decreased.

Impact du traitement carcinologique sur le fonctionnement sexuel et l’image du corps des patientes tunisiennes en rémission d’un cancer du sein localiséImpact of Cancer Treatment on Sexual Functioning and Body Image of Tunisian Patients in Remission from Localized Breast Cancer

The diagnosis and the management of breast cancer(BC)affect in a complex way women’s sexual lives and touch the symbol of femininity,which is very important in the constitution of the body image.Our objectives were to assess the sexual functioning and the body image of patients in remission of localized BC,to determine the links between these two parameters,and to study their relationship with the therapeutic modalities.We conducted a cross-sectional,descriptive,and analytical study in the medical oncology and radiotherapy departments of Habib Bourguiba University Hospital Center in Sfax(Tunisia),between February and August 2022.Patients were assessed based on a clinical information sheet and two psychometric scales exploring sexual functioning and body image:Female Sexual Function Index(FSFI)and Body Image Scale(BIS).The sample comprised 74 patients with a mean age of 51.55 years.They were treated by conservative or radical surgery(44.6%and 55.4%,respectively),chemotherapy(87.8%),hormone therapy(79.7%),targeted therapies(36.5%),and radiotherapy(97.3%).A rate of 51.4%of women had sexual dysfunction(SD),87.8%had hypoactive sexual desire and 36.5%had body image disorder.The body image disorder was significantly associated with DS(p=0.001).The total FSFI score(p=0.001)as well as the subscores of desire(p=0.005),arousal(p=0.003),orgasm(p=0.002),satisfaction(p<0.001),and pain(0.03)were significantly lower in patients with body image disorder.The presence of a SD was not associated with any therapeutic modality.In contrast,the presence of body image disorder was significantly associated with the radical type of surgery(p=0.003)and chemotherapy(p=0.001).Our results showed a relatively high frequency of SD and body image disorder in women in remission from BC.These two parameters seem to be closely linked,and this link would be maintained by mastectomy and chemotherapy,which appear to be therapeutic modalities incriminated in the disturbance of body image.Hence the importance of medical follow-up and psychological support for these operated patients to help them overcome all the physical,psychological,and sexual difficulties to which they are exposed.