Visual Quality Of Stego-image Research Articles

Advanced reversible stenographic method for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm

SummaryIn this article, an advanced reversible stenographic method is proposed for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm. Here, the cover image and secret message are taken as input. In this image, the edges are identified by Canny edge detection system and embedded by the process of dual‐tree complex wave transformation method (DT‐CWT‐CWOA‐SDH) and pixel edges are optimized using the chaos whale optimization algorithm (CWOA), it optimizes the edge pixel variations and maximizes the robustness of the image and visual quality of stego image. The objective of this process is to increase the security of secret data hiding the secret message on cover image and forming the stego image by the embedding procedure and to maximize the peak signal‐to‐noise ratio (PSNR) and reduce the execution time. The proposed method runs on the MATLAB work site and the performance of proposed method is evaluated using different existing methods. The simulation outcomes illustrate that the proposed DT‐CWT‐CWOA‐SDH shows higher PSNR of 32.01%, 24.79%; lower mean square error (MSE) of 21.13%, 45.185%, normalized correlation (NC) of 11.24%, 19.04% compared with existing method.

Robust Method for Embedding an Image inside Cover Image based on Least Significant Bit Steganography

According to the enormous evolution of the internet and communications, the security of private or sensitive information has become the important issue. The private information can be passed between a sender and a receiver with high security using Cryptography and Steganography. By the cryptography, as the information can be secured with the cipher key for encryption. By the Steganography, the secret information can hide within usual data such as images, videos, audios. In this paper we proposed the robust method that includes two phases. The first phase consists of two stages. In the first stage we encrypt a secret image using encryption algorithm in order of increasing security of information. In the second stage, we complete the first stage for embedding the most significant bits (MSB) of the encrypted image into the least significant bits(LSB) of the cover image for instituting the stego image. The second phase is the obverse of the first phase, where, the encrypted image is retrieved from the stego image and then, decrypted process construct the secret image. The proposed method is efficient in terms of security compare with the other methods. Where, both encryption and embedding algorithms have an efficient role for embedding the secret image and preserving the good visual quality of stego images. Furthermore, extraction algorithms obtained better and faster results to a restoration of the secret image.

Image-to-Image Steganography Using Encoder-Decoder Network

In this paper, a convolution neural network is utilized for image-to-image steganography using encoder decoder architecture. A new loss function is designed to improve the invisibility of payload image. The encoder-decoder architecture is used for the image-to-image steganography. The developed architecture is evaluated on the well-known image dataset and compared with the recently developed models. The proposed model was able to withstand the stegoanalyzer attack and better visual quality of stego image. It is able to achieve great imperceptibility.

An enhanced separable reversible and secure patient data hiding algorithm for telemedicine applications

In telemedicine industry, a standout among the most significant issues is the exchange of Electronic Patient Information (EPI) between patient and a doctor that are remotely connected. A minute change to EPI may result in wrong diagnosis to the patient. With the aim to ensure secure and safe communications in telemedicine framework, an enhanced separable reversible data hiding technique in encrypted domain has been presented here that gives high embedding rate by embedding k, (k≥1) binary bits of patient data in base2k numeral framework using Average Pixel Repetition (APR) method. APR method converts original image of size M×N into encrypted scaled-up image of size (2×M−1)×(2×N−1) such that non-seed pixels are used for data embedding where as seed pixels remain as it is to facilitate reversibility. The experimental study shown that the proposed method gave extremely high embedding rates on both natural and medical images. For all test images, the proposed methodology altogether beated all the compared methodologies in its ability to embed patient information and precisely recover it with maintaining the visual quality of stego images too.

An improved separable reversible patient data hiding algorithm for E-healthcare

In the telemedicine industry, a standout among the most significant issue is the exchange of Electronic Patient Information (EPI) between patient and a doctor that are remotely connected. A minute change to EPI may result in a wrong diagnosis for the patient. To ensure secure and safe communication for telemedicine applications, a dual-image separable block-based reversible data hiding algorithm in encrypted domain for embedding secret message in base5 numeral framework is proposed here. The proposed scheme has not been suffering from underflow and overflow problem so that empowering it to embed and recover information precisely from low-intensity pixels too. This property makes our proposed methodology truly reasonable for its utilization on medical images. To prove the effectiveness of our proposed approach, experiments have been performed on different test images. The average PSNR value is 54.10 dB for an embedding capacity of 327,680 bits for all test images which demonstrates that the method is capable of giving good quality stego images even at high payload also. The experimental study revealed that for all types of test images, the proposed methodology altogether beaten all the compared methodologies in its ability to embed secret message and precisely recover it by maintaining the visual quality of stego images too.

An improved reversible and secure patient data hiding algorithm for telemedicine applications

In the telemedicine framework, a standout among the most significant issues is the exchange of electronic patient information (EPI) between patient and a doctor that are remotely connected. A minute change to EPI may result in a wrong diagnosis for the patient. To ensure secure and safe communication for telemedicine applications, an enhanced reversible data hiding method in the encrypted domain has been presented in this paper. All compared reversible data hiding methods have been seen to show predominant outcomes, yet just on natural images not on medical images because underflow problem may arise in medical images due to a large number of pixels have low-intensity values. Thus, an enhanced reversible data hiding method in the encrypted domain has been introduced here that gives a higher embedding rate than all the looked at reversible data hiding methods by embedding k, ( $$k\ge 1$$ ) binary bits of a secret message at every pixel of a cover image without any occurrence of underflow and overflow problem. The proposed method has not been suffering from underflow and overflow problem so that empowering it to embed and recover information precisely from low-intensity pixels too. This property makes our proposed method truly reasonable for its utilization on medical images. For all test images, the proposed method altogether beat all the compared methods in its ability to embed secret information and precisely recover it with maintaining the visual quality of stego images too.

High-Capacity Constructive Steganography Using Optimal Texture Block Synthesis

In this paper, we design a new high-capacity constructive steganographic scheme by optimal texture image block synthesis. First, original texture pattern is divided into multiple seed patches, which are hashed into a blank stego pattern by the key. Furthermore, we employ generated seed patches to reconstruct a candidate pattern, which is scanned by sliding window to generate a series of candidate texture blocks. Subsequently, we sort these candidate texture blocks and select the appropriate ones that their serial number equals to the secret messages to achieve information hiding. After theses texture blocks containing secret messages are hashed into the stego pattern by the key, the remaining positions of stego pattern are sequentially filled with the optimal candidate texture patches by calculating the least square error. Finally, the stego pattern is completely synthesized as the constructive stego image. Compared with the existing schemes, our proposed scheme has a significant high embedding capacity, while keeping a higher visual quality of stego images.

Image Steganography Built on Pixel Value Difference in Spatial Domain using Range Table

With the increase of digital transactions, providing security for the network and its devices is a big challenge today. Sensitive information that has more value in the network is to be protected from unauthorized users in accessing it. Various algorithms are being developed to provide security services for the data. In this paper security is provided by using pixel value differencing technique. Valuable data is embedded in each of the component of color like red, blue and green of a pixel in a color image. In addition to that in providing additional security pixel value has been updated conditionally, that would be more complex to trace the incremented or decremented bits in a pixel of the stegoimage. From this experiment the proposed method provides better visual quality of stego image. This proposed algorithm is suitable for small business applications where small size data is important and threats are more common.

Image steganography using least significant bit and secret map techniques

In steganography, secret data are invisible in cover media, such as text, audio, video and image. Hence, attackers have no knowledge of the original message contained in the media or which algorithm is used to embed or extract such message. Image steganography is a branch of steganography in which secret data are hidden in host images. In this study, image steganography using least significant bit and secret map techniques is performed by applying 3D chaotic maps, namely, 3D Chebyshev and 3D logistic maps, to obtain high security. This technique is based on the concept of performing random insertion and selecting a pixel from a host image. The proposed algorithm is comprehensively evaluated on the basis of different criteria, such as correlation coefficient, information entropy, homogeneity, contrast, image, histogram, key sensitivity, hiding capacity, quality index, mean square error (MSE), peak signal-to-noise ratio (PSNR) and image fidelity. Results show that the proposed algorithm satisfies all the aforementioned criteria and is superior to other previous methods. Hence, it is efficient in hiding secret data and preserving the good visual quality of stego images. The proposed algorithm is resistant to different attacks, such as differential and statistical attacks, and yields good results in terms of key sensitivity, hiding capacity, quality index, MSE, PSNR and image fidelity.

An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography

Content-adaptive steganography intends to hide data in the complex texture content of the image. Recently, some secure steganography methods have been proposed to identify the textural complexity of an image. However, most of the techniques do not take into account the information of pixel variation around the central pixel in all possible directions and therefore they are unable to accurately analyse the texture complexity. This work offers a quality-enhanced and secure method of content-adaptive image steganography. The proposed method is divided into three sequential steps: image segmentation, pixel complexity identification, and data embedding. An input cover image is initially divided into small local regions and the pixel-complexity is identified based on the proposed Complex Block Prior (CBP) criterion. In a local block, a high pass filter (HPF) bank is applied and eight residual responses are obtained. Following the CBP criterion, a complexity level out of nine levels is assigned to an individualized pixel block. The pixels are then arranged in the priority of complexity from highest to lowest. Data embedding for the corresponding complexity level then takes place using the proposed adaptive embedding algorithm. Experimental results verify the preservation of visual quality of stego images produced by the proposed method. Three image datasets: Standard test images, BOWS2 and BOSS-base are used for the experimentation and comparison with prior state-of-art methods. Highest values of the IQ (image quality) parameters e.g., SSIM and WPSNR show the effectiveness of the proposed method.

Reversible data hiding in binary images based on image magnification

Over the past few years, many methods have been proposed for reversible data hiding in digital images, but few have been applied to binary images. The existing methods mainly employ run-length to embed the secret message, but the capacity is low. In this paper, we propose a reversible data hiding method based on image magnification. Firstly, image cross-shape patterns are analyzed to select the reference block pattern. Then, to improve the capacity and ensure reversibility, an image magnification strategy based on the reference block pattern is designed to scale up the original image to get the reference image. Finally, to ensure the visual quality of stego image, an inner-block flippable pixel selection strategy is designed to embed data. Experimental results have demonstrated that the proposed reversible data hiding scheme can restore the original image after extracting the embedded message, and achieve high embedding capacity and good visual quality.

Hiding clinical information in medical images: An encrypted dual-image reversible data hiding algorithm with base-3 numeral framework

In current scenario, dual-image reversible data hiding techniques (RDH) have become very popular due to their ability to give more embedding rate and improved visual quality of stego images than conventional RDH algorithms. All these methods have been observed to exhibit superior results, but only on natural images. In case of the medical images, there is an inherent risk of underflow, since a lot of pixels tend to have low intensity value. So, a novel encrypted dual image reversible data hiding algorithm has been presented here that gives higher embedding rate than all the existing dual-image reversible data hiding algorithms by changing over secret binary message into base-3 numeral framework without any underflow issue. The reported results reveal that the proposed algorithm gave very high embedding rates on both natural and medical images. The embedding rates on medical images have been significantly higher than all the compared approaches. The proposed approach yielded an embedding rate of 1.53 bits per pixel for medical images, almost double than most of the existing methods.

Image Steganography Using DWT and Semi Hexadecimal Code Based on PSNR

In this paper, a novel image steganography approach is proposed to enhance the visual quality of stego image. The cover image is decomposed using Discrete Wavelet Transform (DWT) to produce wavelet subbands and threshold value is calculated for each higher frequency wavelet subbands. Wavelet coefficients having magnitude larger than the threshold of its subband are selected to embed the secret data. Semi Hexadecimal Code (SHC) is proposed to convert pixel value of secret image into smaller equivalent value so that it distorts stego image as less as possible. Experimental results shows that maximum PSNR between cover image and stego image is more than 75 dB .Proposed approach is also compared with the existing approaches and this comparison shows that the proposed approach is better than the existing approaches.

A novel reversible data hiding scheme with two-dimensional histogram shifting mechanism

In this paper, we propose a novel reversible data hiding technique based on two-dimensional histogram shifting for quantized discrete cosine transformation coefficients (QDCT). In the proposed scheme, a two-dimensional histogram is constructed by QDCT coefficients blocks with the size of 8 × 8 of the left image and the right image. Once most of the QDCT coefficients are located at the top-right corner of the two-dimensional histogram, the QDCT coefficients are selected for embedding data to achieve high embedding capacity. In the embedding procedure, the three main steps, i.e., expanding, shifting, and embedding, are only used for QDCT coefficients in this corner not only to gain embedding capacity, but also to maintain good visual quality of stego images. The experimental results demonstrated that the proposed scheme is superior to the previous schemes in terms of embedding capacity and image quality.

Local complexity based adaptive embedding mechanism for reversible data hiding in digital images

In this paper, a reversible data hiding scheme for digital images with high hiding capacity is proposed. Original image is segmented into smooth and rough regions based on local complexity. In order to achieve higher hiding capacity, we embed three bits into each pixel belonging to smooth region with lower local complexity and one bit is embedded into each pixel of rough region, which can effectively exploit more redundancy during data embedding compared with conventional methods of prediction error expansion (PEE). Additionally, the pixel selection mechanism is applied to reduce the number of shifted pixels, which leads to high visual quality of stego image. Experimental results show that, our scheme can achieve better rate-distortion performance than some of state-of-the-art schemes.

Enhanced encrypted reversible data hiding algorithm with minimum distortion through homomorphic encryption

Reversible data hiding means embedding a secret message in a cover image in such a manner, to the point that in the midst of extraction of the secret message, the cover image and, furthermore, the secret message are recovered with no error. The goal of by far most of the reversible data hiding algorithms is to have improved the embedding rate and enhanced visual quality of stego image. An improved encrypted-domain-based reversible data hiding algorithm to embed two binary bits in each gray pixel of original cover image with minimum distortion of stego-pixels is employed in this paper. Highlights of the proposed algorithm are minimum distortion of pixel’s value, elimination of underflow and overflow problem, and equivalence of stego image and cover image with a PSNR of ∞ (for Lena, Goldhill, and Barbara image). The experimental outcomes reveal that in terms of average PSNR and embedding rate, for natural images, the proposed algorithm performed better than other conventional ones.

Improving stego image quality in image interpolation based data hiding

Jung and Yoo proposed a new image interpolation method, neighbor mean interpolation, on which they first constructed image interpolation based data hiding (IIDH) scheme. However, the authors only adopted a simple method by adding the decimal value of secret into pixels in cover image. Therefore, even though neighbor mean interpolation method is very cost effective, Jung and Yoo's IIDH scheme does not have very high-resolution stego image. In this paper, we still use neighbor mean interpolation (NMI) to generate cover image, but adopt least significant (LSB) substitution and optimal pixel adjustment process (OPAP) instead of simple addition to improve visual quality of stego image. The main contribution of this paper is to prove theoretically that our IIDH schemes have the better stego image quality than Jung and Yoo's IIDH scheme.

Block-Based High Capacity Multilevel Image Steganography

This paper proposes a block-based high capacity steganography technique for digital images. The cover image is decomposed into blocks of equal size and the largest pixel of each block is found to embed the secret data bits and also the smallest pixel of each block is used for embedding to enhance the capacity. Embedding of secret data is performed using the concept that the pixel of a cover image has only two states — even and odd. Multilevel approach is also combined in the proposed technique to achieve high embedding capacity. In order to make the proposed technique more secure, a key is generated using embedding levels, block size, pixel embedding way, encryption parameters, and starting blocks of each embedding levels. Embedding capacity and visual quality of stego images generated by the proposed steganography technique are higher than the existing techniques. Steganalysis tests have been performed to show the un-detectability and imperceptibility of the proposed technique.

COMPARATIVE STUDY OF EDGE BASED LSB MATCHING STEGANOGRAPHY FOR COLOR IMAGES

Steganography is a very pivotal technique mainly used for covert transfer of information over a covert communication channel. This paper proposes a significant comparative study of the spatial LSB domain technique that focuses on sharper edges of the color as well as gray scale images for the purpose of data hiding and hides secret message first in sharper edge regions and then in smooth regions of the image. Message embedding depends on content of the image and message size. The experimental results illustrate that, for low embedding rate the method hides the message in sharp edges of cover image to get better stego image visualization quality. For high embedding rate, smooth regions and edges of the cover image are used for the purpose of data hiding. In this steganography method, color image and textured kind of image preserves better visual quality of stego image. The novelty of the comparative study is that, it helps to analyze the efficiency and performance of the method as it gives better results because it directly works on color images instead of converting to gray scale image

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent techniques