Algorithm For Color Images Research Articles

CSENMT: A deep image compressed sensing encryption network via multi-color space and texture feature

In recent years, the rapid development of wireless communication technology has provided great convenience for human information transmission. Color images have become an important data dissemination and sharing medium due to their large amount of information, vivid and intuitive content. However, color images are easily attacked by third-party illegal users during transmission over public channels and storage in the cloud, and the large image size leads to occupying too many channel resources. Therefore, a deep image compressed sensing encryption network using multi-color space and texture feature (CSENMT) is proposed. Specifically, a multi-color space sampling network based on sparse matrix is presented to obtain the measurement of plain image, and the measurement is shuffled by an adaptive permutation based on chaotic system and plain image (APCP). On the decryption end, the decryption party inversely scrambles the cipher image to obtain the decrypted measurement, and sends it to a deep reconstruction based on multi-color space and texture information (DRMST) to gain the final decrypted reconstructed image. Herein, DRMST can realize high visual performance by using the difference and inter-correlations of several color spaces. Besides, the proposed texture extraction module can focus on extracting texture features to improve the texture details of the reconstructed image. In addition, APCP achieves a higher scrambling degree compared with channel-by-channel permutation. Experimental results demonstrate the advantages of our algorithm for color images in visual performance, efficiency and security.

Blind Extraction of Digital Watermarking Algorithm for Color Images

Digital watermark technology hides copyright information in digital images, effectively protecting the copyright of digital images. At present, the color image digital watermarking algorithm still has defects such as the inability to balance robustness, invisibility and the weak anti-attack ability. Aiming at the above problems, this paper studies the digital watermarking method based on discrete wavelet transform and discrete cosine transform. Then this paper proposes a color image blind digital watermarking algorithm based on QR code. First, convert the color image from RGB space to YCbCr space, extract the Y component and perform the second-level discrete wavelet transform. secondly, block the LL2 subband and perform the discrete cosine transform. finally, use the embedding method to convert the watermark information after the Arnold transform embedded in the block. The experimental results show that the PSNR of the color image embedded with the QR code is 56.7159 without being attacked. After being attacked, its PSNR and NC values are respectively 30dB and 0.95 or more, which proves that the algorithm has good robustness and can achieve watermarking blind extraction.

Blind Extraction of Digital Watermarking Algorithm for Color Images

Blind Extraction of Digital Watermarking Algorithm for Color Images

Sketch Based Data Retrieval Using Reversible Data Hiding on Images

Sketch Based Image Retrieval as name suggests is a branch of image retrieval that searches the images based on sketches. The sketches bridge the gap between imagination and real images. Sketches act as powerful searching tool in image retrieval. It efficiently uses the data hiding technique, which is a watermarking technique and can be used for embedding messages into images. A message can be embedded into color images without changing its grayscale version. Embedding of messages was thus done using unchanged gray version. It can also extract the messages. This unchanged grayscale version is maintained from message embedding to extraction process. This concept of watermarking generates SBIDR valuable, because many applications or algorithms for color images are based on its corresponding grayscale version. Embedding of data is carried out into in three-color channels of color image and in gray value of Sketch Image. Sketch image is encrypted with key, which will be required at the time of message extraction process after SBIR. In this way grayscale invariance is maintained which made the Sketch Based Retrieval more effective.

Performance and analysis of high capacity Steganography of color images involving Wavelet Transform

This paper proposes a modified and simple method for high capacity Steganography in case of color images. This algorithm is usually based on the wavelet fusion technique which was not attempted for color images and it proves to be a simplest method than other techniques or algorithms for color images. Even though it uses transform domain technique which only provides robustness against attacks and eavesdropping and it is known that spatial domain techniques usually meet the capacity and quality requirements. In this paper the transform domain technique (Wavelet Transform) is used to attain high capacity along with security and maintains the quality of the cover image which acts as the key feature of this work. This improvement in the capacity–quality tradeoff is analyzed and proved experimentally in this paper and various image quality parameters have been evaluated to prove the above.

An Improved Algorithm for Color Medical Image Compression Based on DCT

Medical image compression technology has great significance in the field of medical image engineering and clinical application. The current image compression technology is mainly for gray image, Few people study on medical image color compression algorithm. This paper presents a compression algorithm for color image based on DCT. First, the algorithm change the color medical image of RGB space to SAT space, this transformation ensures the medical image without distortion, and effectively reduce the mean image of each dimension of component. Then, the algorithm make the DCT transform for color image compression in the SAT space. Experimental shows that the improved algorithm in color medical image compression has achieved good results.

Image Tampering Detection and Repairing

It is very crucial to design efficient methods to provide authentication to document images mainly for images whose security must be protected. In digital media the authentication, tampering detection and repairing of the tampered data is main concern. Nowadays many digital documents are transferred on the internet regularly e.g. circuit diagrams, scanned cheques, signed documents, drawings, design drafts etc. Here the method of image authentication, tampering detection and repairing is explained. The grayscale image document image authentication with self repair method is provided. The authentication signal is calculated from binary image of the original document image. Secret sharing scheme is used to calculate this authentication signal. The extra alpha channel is embedded in the original grayscale document image. The calculated authentication signal is then embedded in this alpha channel. This is one of the way of visual cryptography in which image is visible but authentication signal will not be recognized. Then this authentic image is encrypted for better security. this whole procedure is done at sender side. In second module i.e. receiver side the image is decrypted. Then the embedded authentication signal is extracted from the received authentic image. The new authentication signal is calculated from the binary image of the received authentic image. This new authentication signal is compared with the extracted signal and the integrity check is provided. If data modification is detected, then the method is proved to repair the tampered pixels using the reverse secret sharing method. The tampering of data is detected successfully in this method without any original image backup. This type of secret sharing scheme is helpful for reducing the risk of incidental partial data loss. This method is also applicable to the color image. Algorithm for color image is also same as grayscale images. In this paper the result is provided only for the grayscale images and supposed to expand for color images as well.

Iterative filtering algorithm for color image based on visual sensitivity and improved directional distance

To eliminate the influence of visual difference on color image filtering, a method to compute the visual sensitivity value of three primary colors was given. The filter algorithm detected pixels by rough set first, then used visual sensitivity to correct the test results, finally filtered the noise pixels by the improved Directional Distance Filter( DDF). The experimental results show that the new filter, compared with several other representative vector filters, provides better performance on color keeping, edge detail preservation, and noise filtering rate. In addition, the normalized mean square error of our method is the smallest and the Peak Signal-to-Noise Ratio( PSNR) is the largest under different noise density.

Extraction of color image texture feature based on gray-level co-occurrence matrix

Texture plays a very important role in image retrieval and classification,and texture feature extraction has been a research hotspot. Most present existing texture extraction algorithms can be only used to calculate texture features of gray image. Texture extraction algorithm for color image is very few. Referring to the analytical method of gray level co- occurrence matrix( GLCM),the authors analyzed the influence law of parameters( direction, distance,grayscale,window size) on GLCM texture features of color image. A color image texture feature extraction method( color GLCM,CGLCM) based on GLCM was realized. Through analyzing the influence law of these parameters on four texture features( ASM( angular second moment),Entropy,Contrast,Correlation),a proper parameter value range was given and the CGLCM method was optimized. The results of comparing CGLCM method with GLCM method show that the four texture features calculated with CGLCM method have better robustness and identification capability. These results can provide reference for image retrieval and classification based on texture information.

Color image quality assessment algorithm based on color structural similarity

Concerning the disadvantages of quality assessment algorithms for color images,a new algorithm based on visual structural similarity was proposed.Firstly,testing images were transformed into a selected uniform color space LAB2000HL.Secondly,one luminance Contrast Sensitivity Function(CSF) and two chromatic CSFs were used to filter images respectively.Thirdly,three structural similarity indexes were computed by multi-scale structural similarity index measurement(M-SSIM).Lastly,the proposed algorithm was constructed by weighting the three structural similarity indexes,which depended on different visual sensitivities of luminance and chromaticity.In the experiment,testing results on TID2008 database were compared with the results of visual assessment by Spearman rank-order correlation coefficient and Kendall rank-order correlation coefficient.The experimental results show that the proposed algorithm is more consistent with visual assessment and outperforms several other popular image quality assessment algorithms.

Blind Watermarking Algorithm for Color Images Based on Nearest Neighbor Interpolation

In this paper, we present a blind digital watermarking method for color image based on nearest neighbor interpolation. The algorithm has the following characteristics: (1) it generate adaptive watermark based on the size of carrier image,so as to improve the robustness of binary watermark; (2) the watermark is embedded in the DCT coefficient of intermediate frequency, which can effectively resist common attacks, such as Gaussian noise-adding, salt and pepper noise-adding, cropping, Wiener filtering, JPEG compression;(3) the watermarking detection is simple and fast, and does not require carrier image. The experiments show that the algorithm has good invisibility and strong robustness.

Encryption and Compression Scheme of Color Image Based on a Hyperchaotic System

In order to encrypt and compress a color image simultaneously, an encryption and compression algorithm for color image was proposed based on a hyperchaotic system. A hyperchaotic system was utilized to make a pure white image into a uniform distribution and colorful palette. In compression process, indexing technology was utilized to map the 3D data of color image to two-dimensional subscript of palette. The compressed image would continue to be encrypted by loop feedback in physical space and time space. Simulation experiments show that the algorithm is realized to encrypt and compress a color image simultaneously. It has large key space, high security, and big compression ratio as well as great application value in secure communication of color image.

A Digital Watermarking Algorithm for Color Image Based on DWT

An efficient digital watermark embedding algorithm for color image was presented in this paper, which is based on the discrete wavelet transform (DWT) and the spectral characteristics of human vision system. Firstly, three color separations was performed for color image, and color components of color image were transformed by DWT. Secondly, the embedding position of the watermark was confirmed by comparing the energy value of the low frequency sub-band in the transformed blue component and green component. Thirdly, the watermark was made Arnold Transform for encryption and was embedded in the color component with a larger power. Finally, this paper made the simulation experiments to evaluate the performance of the watermark. The simulation results showed that the embedded watermark had good invisibility and robustness for the common image processing, such as filtering, noise, especially compression and cropping. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2681 Full Text: PDF

Large-capacity blind steganography algorithm for color images based on visual perception mechanism

Most existing steganography algorithms for color images are designed by directly applying steganography for gray-scale images to color channel without employing color visual perception mechanism.A large-capacity blind steganography algorithm for color images based on visual perception mechanism in YUV space was proposed.The main idea is to analyze the local complexity of the carrier image via standard deviation on the Y component,split the message into two parts using the color visual perception mechanism,and then hide them in Y and V components respectively.Being less flexible,the U component was simply used as an information indicator.A large number of experiments were carried out showing that the proposed algorithm still maintains good imperceptibility compared with other methods after embedding large-capacity information,and can resist both the histogram contrast and RS steganalysis.Thus,the proposed algorithm is reasonable,easy to implement,and effective.

Enhancement algorithm for color images based on co-occurrence matrix

Considering that the traditional method of histogram equalization can make the image produce unnatural enhanced results,a new color image contrast enhancement approach was proposed,which equalized color components by dependently using co-occurrence matrix.Firstly,gray correlative characteristics of pixels were combined in 3×3 neighborhoods to construct a co-occurrence matrix.Secondly,the method of co-occurrence histogram equalization was applied to luminance component only and the chrominance components were preserved.Finally,dark channel prior was used to solve the problem mentioned above to obtain the ideal image.Comparing the proposed enhanced algorithm with the other three typical enhancement algorithms,it is shown that the proposed algorithm not only considers the whole and local image information,but also deals with the histogram spikes and halo effect.The experimental results demonstrate that the proposed method can enhance the color images effectively.

Reversible data hiding scheme for color image based on prediction-error expansion and cross-channel correlation

In this paper, we present a reversible data hiding (RDH) algorithm for color image. The traditional RDH technique regarding color image embeds data into each color channel independently. Considering that the color channels correlate with each other, we propose a RDH algorithm based on prediction-error expansion that can enhance the prediction accuracy in one color channel through exploiting the edge information from another channel. By doing so, the entropy of the prediction-error is decreased statistically, and consequently, the algorithm efficiency is increased in terms of data hiding rate versus embedding distortion. Extensive experimental results demonstrate that the proposed algorithm outperforms the traditional RDH methods independently embedding data into each channel.

A Watermarking Algorithm Based on Wavelet and Hadamard Transform for Color Image

Digital image watermarking is a useful solution to the problem of information security, copyright and network security. In this paper, we propose a watermarking algorithm for color image based HT and DWT. A binary image as watermark is embedded into green component or blue component of color image. The algorithm can satisfy the transparence and robustness of the watermarking system very well. The experiment based on this algorithm demonstrates that the watermarking is robust to the common signal processing techniques including JPEG compressing, adding noise, low pass filter, and mosaic.

Distribution Key in Eight Bit's Color Image Algorithm

Problem statement: The networked multimedia systems have glorified the necessity for image copyright protection. To solve such problem an invisible structure called watermarking is added to an 8-bits color image in aim to mark it. The structure can be added by selecting bits under certain conditions; a few pixels of correspondence between the image and the ASSCI code. Approach: In this study, we employed a robust image-watermarking algorithm using the Key Distribution Algorithm to hide data inside 8-bits color image as a watermark. Results: Experimental results show that, Similarity in the embedding process making the selection bits from the image and did not make any change in the pixels, Entropy become equal zero where no changes in the existed pixels and the selected keys chosen from pixels which distributed in image, where does not exist any changed on cover image so any updating on image doesn’t mean anything, so the key of the owner cannot be known. Conclusion: By applying Key Distribution algorithm the watermark can be extracted at low error rate.

Enhancing the Color Set Partitioning in Hierarchical Tree (SPIHT) Algorithm Using Correlation Theory

Problem statement: Efficient color image compression algorithm is essential for mass storage and the transmission of the image. The compression efficiency of the Set Partitioning in Hierarchical Tree (SPIHT) coding algorithm for color images is improved by using correlation theory. Approach: In this study the correlation between the color channels are used to propose the new algorithm. The correlation between the color channels are analyzed in various color spaces and the color space CIE-UVW in which the color channels are highly correlated is taken. The most correlated U channel is considered as base color and compressed by using the wavelet filter and the SPIHT algorithm. The linear approximation of the two of the color components (V and W) based on the primary color component U is used to code subordinate color components. The image is divided into N*N blocks in each color channels. The linear approximation coefficients are calculated for each block of the subordinate colors V and W as functions of the base color. Only these coefficients of each block are coded and send to the receiver along with the SPIHT coding of the base color. Results: By using this algorithm, a significant (4 dB mean value) Peak Signal to Noise Ratio (PSNR) improvement is obtained compared to the traditional coding scheme for the same compression rate and reduces the coding and decoding time. Also the proposed compression algorithm reduces the complexity in coding and decoding algorithms. Conclusion: This algorithm allows the reduction of complexity for both coding and decoding of color images. It is concluded that a significant PSNR gain and visual quality improvement is obtained. It is found that in color image coding, this algorithm is superior to the traditional de-correlation based methods and reduces the coding and decoding time.

Non-linear scaling algorithm based on potential energy of color images

Non-linear scaling can maintain the main characteristics and the ratio of the image.Based on the image gradient function,a new potential energy algorithm for color images was proposed in RGB model,and the strong regions were found using potential energy.Fast linear interpolation scaling was used in low energy regions,and it preserved those strong areas in order to protect important features of the image objects.Compared with the traditional image scaling algorithm,the proposed algorithm can overcome the shortcomings of image distortion generated by the scaling effectively.