scholarly journals Improved Reference Image Encryption Methods Based on 2K Correction in the Integer Wavelet Domain

2019 ◽  
Vol 29 (4) ◽  
pp. 817-829 ◽  
Author(s):  
Turker Tuncer ◽  
Sengul Dogan ◽  
Ryszard Tadeusiewicz ◽  
Paweł Pławiak
Keyword(s):  
Image Encryption ◽  
Signal To Noise Ratio ◽  
Visual Quality ◽  
Reference Image ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Encrypted Image ◽  
Reference Images ◽  
Integer Wavelet

Abstract Many visually meaningful image encryption (VMIE) methods have been proposed in the literature using reference encryption. However, the most important problems of these methods are low visual quality and blindness. Owing to the low visual quality, the pre-encrypted image can be analyzed simply from the reference image and, in order to decrypt nonblind methods, users should use original reference images. In this paper, two novel reference image encryption methods based on the integer DWT (discrete wavelet transform) using 2k correction are proposed. These methods are blind and have high visual quality, as well as short execution times. The main aim of the proposed methods is to solve the problem of the three VMIE methods existing in the literature. The proposed methods mainly consist of the integer DWT, pre-encrypted image embedding by kLSBs (k least significant bits) and 2k correction. In the decryption phase, the integer DWT and pre-encrypted image extraction with the mod operator are used. Peak signal-to-noise ratio (PSNR) measures the performances of the proposed methods. Experimental results clearly illustrate that the proposed methods improve the visual quality of the reference image encryption methods. Overall, 2k correction and kLSBs provide high visual quality and blindness.

FUSION OF SURVEILLANCE IMAGES IN INFRARED AND VISIBLE BAND USING CURVELET, WAVELET AND WAVELET PACKET TRANSFORM

2010 ◽  
Vol 08 (02) ◽  
pp. 271-292 ◽  
Author(s):  
PARUL SHAH ◽  
S. N. MERCHANT ◽  
U. B. DESAI
Keyword(s):  
Wavelet Packet ◽  
Curvelet Transform ◽  
Visual Quality ◽  
Wavelet Packet Transform ◽  
Discrete Wavelet ◽  
Discrete Wavelet Packet Transform ◽  
Fused Image ◽  
Fusion Methods ◽  
Visible Images

This paper presents two methods for fusion of infrared (IR) and visible surveillance images. The first method combines Curvelet Transform (CT) with Discrete Wavelet Transform (DWT). As wavelets do not represent long edges well while curvelets are challenged with small features, our objective is to combine both to achieve better performance. The second approach uses Discrete Wavelet Packet Transform (DWPT), which provides multiresolution in high frequency band as well and hence helps in handling edges better. The performance of the proposed methods have been extensively tested for a number of multimodal surveillance images and compared with various existing transform domain fusion methods. Experimental results show that evaluation based on entropy, gradient, contrast etc., the criteria normally used, are not enough, as in some cases, these criteria are not consistent with the visual quality. It also demonstrates that the Petrovic and Xydeas image fusion metric is a more appropriate criterion for fusion of IR and visible images, as in all the tested fused images, visual quality agrees with the Petrovic and Xydeas metric evaluation. The analysis shows that there is significant increase in the quality of fused image, both visually and quantitatively. The major achievement of the proposed fusion methods is its reduced artifacts, one of the most desired feature for fusion used in surveillance applications.

scholarly journals Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5540
Author(s):  
Nayeem Hasan ◽  
Md Saiful Islam ◽  
Wenyu Chen ◽  
Muhammad Ashad Kabir ◽  
Saad Al-Ahmadi
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Reconstructed Image ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Watermarking Scheme

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.

scholarly journals A Novel Consistent Quality Driven for JEM Based Distributed Video Coding

Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 130 ◽  
Author(s):  
Dinh Trieu Duong ◽  
Huy Phi Cong ◽  
Xiem Hoang Van
Keyword(s):  
Video Coding ◽  
Signal To Noise Ratio ◽  
Video Quality ◽  
Visual Quality ◽  
Low Complexity ◽  
Distributed Video Coding ◽  
Surveillance Systems ◽  
Promising Solution ◽  
Optimal Values

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.

scholarly journals Free-viewpoint image synthesis using superpixel segmentation

2017 ◽  
Vol 6 ◽  
Author(s):  
Mehrdad Panahpour Tehrani ◽  
Tomoyuki Tezuka ◽  
Kazuyoshi Suzuki ◽  
Keita Takahashi ◽  
Toshiaki Fujii
Keyword(s):  
Three Dimensional ◽  
Image Synthesis ◽  
Physical Distance ◽  
Depth Image ◽  
Reference Image ◽  
Sampling Density ◽  
Superpixel Segmentation ◽  
Limited Sampling ◽  
Reference Images

A free-viewpoint image can be synthesized using color and depth maps of reference viewpoints, via depth-image-based rendering (DIBR). In this process, three-dimensional (3D) warping is generally used. A 3D warped image consists of disocclusion holes with missing pixels that correspond to occluded regions in the reference images, and non-disocclusion holes due to limited sampling density of the reference images. The non-disocclusion holes are those among scattered pixels of a same region or object. These holes are larger when the reference viewpoints and the free viewpoint images have a larger physical distance. Filling these holes has a crucial impact on the quality of free-viewpoint image. In this paper, we focus on free-viewpoint image synthesis that is precisely capable of filling the non-disocclusion holes caused by limited sampling density, using superpixel segmentation. In this approach, we proposed two criteria for segmenting depth and color data of each reference viewpoint. By these criteria, we can detect which neighboring pixels should be connected or kept isolated in each references image, before being warped. Polygons enclosed by the connected pixels, i.e. superpixel, are inpainted by k-means interpolation. Our superpixel approach has a high accuracy since we use both color and depth data to detect superpixels at the location of the reference viewpoint. Therefore, once a reference image that consists of superpixels is 3D warped to a virtual viewpoint, the non-disocclusion holes are significantly reduced. Experimental results verify the advantage of our approach and demonstrate high quality of synthesized image when the virtual viewpoint is physically far from the reference viewpoints.

scholarly journals Full Reference-Image Quality Assessment with Global and Local Image Regions for Visual Quality Perception and Optimization

2019 ◽  
Vol 8 (6S4) ◽  
pp. 352-356
Keyword(s):  
Quality Assessment ◽  
Image Quality Assessment ◽  
Optimization Problems ◽  
Visual Quality ◽  
Reference Image ◽  
Mathematical Methods ◽  
Mathematical Properties ◽  
Global And Local ◽  
Local Image

Quality Assessment (IQA) by using mathematical methods is offering favorable results in calculating visual quality of distorted images. These methods are developed by examining effective features that are compatible with characteristics of Human Visual System (HVS). But many of those methods are difficult to apply for optimization problems. This paper presents DCT based metric with easy implementation and having mathematical properties like differentiability, convexity and valid distance metricability to overcome the optimization problems. By using this method we are able to calculate the quality of image as a whole as well as the quality of local image regions.

scholarly journals Multi-Image Hiding Blind Robust RGB Steganography in Transform Domain

2020 ◽  
Vol 15 (1) ◽  
pp. 24-52
Author(s):  
Diptasree Debnath ◽  
Emlon Ghosh ◽  
Barnali Gupta Banik
Keyword(s):  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Visual Cryptography ◽  
Structural Similarity ◽  
Histogram Equalization ◽  
Image Steganography ◽  
Digital Data ◽  
Discrete Wavelet ◽  
Discrete Cosine Transformation

Steganography is a widely-used technique for digital data hiding. Image steganography is the most popular among all other kinds of steganography. In this article, a novel key-based blind method for RGB image steganography where multiple images can be hidden simultaneously is described. The proposed method is based on Discrete Cosine Transformation (DCT) and Discrete Wavelet Transformation (DWT) which provides enhanced security as well as improve the quality of the stego. Here, the cover image has been taken as RGB although the method can be implemented on grayscale images as well. The fundamental concept of visual cryptography has been utilized here in order to increase the capacity to a great extent. To make the method more robust and imperceptible, pseudo-random number sequence and a correlation coefficient have been used for embedding and the extraction of the secrets, respectively. The robustness of the method is tested against steganalysis attacks such as crop, rotate, resize, noise addition, and histogram equalization. The method has been applied on multiple sets of images and the quality of the resultant images have been analyzed through various matrices namely ‘Peak Signal to Noise Ratio,' ‘Structural Similarity index,' ‘Structural Content,' and ‘Maximum Difference.' The results obtained are very promising and have been compared with existing methods to prove its efficiency.

scholarly journals High-Capacity Image Steganography with Minimum Modified Bits Based on Data Mapping and LSB Substitution

2018 ◽  
Vol 8 (11) ◽  
pp. 2199 ◽  
Author(s):  
Abdul Zakaria ◽  
Mehdi Hussain ◽  
Ainuddin Wahab ◽  
Mohd Idris ◽  
Norli Abdullah ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
High Capacity ◽  
Visual Quality ◽  
Data Mapping ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Mapping Strategy ◽  
Lsb Substitution

Steganography is the art and practice of communication using hidden messages. The least significant bits (LSB) based method is the well-known type of steganography in the spatial domain. Usually, achieving the larger embedding capacity in LSB-based methods requires a large number of LSB bits modification which indirectly reduces the visual quality of stego-image and increases the risk of steganalysis detection attacks. In this study, we propose a novel steganography method with data mapping strategy which can reduce the number of bits modification per pixel. In the proposed method, four secret data bits are mapped with the four most significant bits of a cover pixel. Furthermore, the only two LSBs of a pixel are modified to indicate the mapping strategy. Experimental results show that the proposed method is able to achieve 3.48% larger embedding capacity while enhancing the visual quality (i.e., peak signal to noise ratio (PSNR) 3.73 dB) and reducing the modification of 0.76 bits per pixel. Moreover, the proposed method provides security against basic Regular and Singular groups (RS) steganalysis and histogram steganalysis detection attacks.

scholarly journals A Reference-Guided Double Pipeline Face Image Completion Network

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1969
Author(s):  
Hongrui Liu ◽  
Shuoshi Li ◽  
Hongquan Wang ◽  
Xinshan Zhu
Keyword(s):  
Signal To Noise Ratio ◽  
Receptive Fields ◽  
Similarity Index ◽  
Face Image ◽  
Reference Image ◽  
Image Completion ◽  
Generative Adversarial Network ◽  
Identity Information ◽  
Adversarial Network ◽  
Reference Images

The existing face image completion approaches cannot be utilized to rationally complete damaged face images where their identity information is completely lost due to being obscured by center masks. Hence, in this paper, a reference-guided double-pipeline face image completion network (RG-DP-FICN) is designed within the framework of the generative adversarial network (GAN) completing the identity information of damaged images utilizing reference images with the same identity as damaged images. To reasonably integrate the identity information of reference images into completed images, the reference image is decoupled into identity features (e.g., the contour of eyes, eyebrows, nose) and pose features (e.g., the orientation of face and the positions of the facial features), and then the resulting identity features are fused with posture features of damaged images. Specifically, a lightweight identity predictor is used to extract the pose features; an identity extraction module is designed to compress and globally extract the identity features of the reference images, and an identity transfer module is proposed to effectively fuse identity and pose features by performing identity rendering on different receptive fields. Furthermore, quantitative and qualitative evaluations are conducted on a public dataset CelebA-HQ. Compared to the state-of-the-art methods, the evaluation metrics peak signal-to-noise ratio (PSNR), structure similarity index (SSIM) and L1 loss are improved by 2.22 dB, 0.033 and 0.79%, respectively. The results indicate that RG-DP-FICN can generate completed images with reasonable identity, with superior completion effect compared to existing completion approaches.

IMAGE IMPROVEMENT IN THE WAVELET DOMAIN FOR OPTICAL COHERENCE TOMOGRAMS

2011 ◽  
Vol 04 (01) ◽  
pp. 73-78 ◽  
Author(s):  
YINGLI WANG ◽  
YANMEI LIANG ◽  
JINGYI WANG ◽  
SHU ZHANG
Keyword(s):  
Signal To Noise Ratio ◽  
Wavelet Denoising ◽  
Processing Method ◽  
Optical Coherence ◽  
Context Modeling ◽  
Wavelet Domain ◽  
Signal To Noise ◽  
Contrast Measure ◽  
Image Improvement

In this paper, an image processing method for improving the quality of optical coherence tomography (OCT) images is proposed. Wavelet denoising based on context modeling and contrast enhancement by means of the contrast measure in the wavelet domain is carried out on the OCT images in succession. Three parameters are selected to assess the effectiveness of the method. It is shown from the results that the proposed method can not only enhance the contrast of images, but also improve signal-to-noise ratio. Compared with two other typical algorithms, it has the best visual effect.

scholarly journals De-noising of MRI Images in Wavelet Domain

2019 ◽  
Vol 8 (4) ◽  
pp. 1947-1949
Keyword(s):  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
The Body ◽  
Medical Procedure ◽  
Wavelet Domain ◽  
Radio Waves ◽  
Resonance Imaging ◽  
Adaptive Histogram Equalization ◽  
Magnetic Resonance Imaging Mri

Magnetic resonance imaging (MRI) is a diagnostic medical procedure that utilizes solid attractive fields and radio waves to deliver definite pictures of within the body. Extensive research has been completed into whether the attractive fields and radio waves utilized during MRI sweeps could represent a hazard to the human body. No proof has been found to propose there's a hazard, which means MRI outputs are one of the most secure restorative methodology accessible. MRI has several advantages which make it ideal in numerous situations, in particular, it can identify small changes of structures inside the body. The disadvantage is the noise that degrades the quality of the image. A threestep processing algorithm is proposed to reduce this noise. Here, first it includes soft thresholding in wavelet domain where the original image is divided into blocks that do not overlap. Then it includes restoration of the object boundaries and texture which are lost as a result of the first step and finally enhancing the image using CLAHE (Contrast Limiting Adaptive Histogram Equalization). It is then analyzed using the error parameters like peak signal to noise ratio and mean square error.

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