Cloud computing is a major blooming technology which has numerous applications in today’s market and is rightly so hyped. Images are a major part of today’s internet data traffic, especially due to widespread social media, and hence, its security is crucial. However, in the present scenario, the images in cloud are a major issue in terms of security. Since the user who has uploaded the image has no control over the security of images, the cloud provider has to ensure maximum security in terms of authentication and prevention from attacks. The main objective of this paper is to provide a method to enhance the safety of images on cloud. This paper presents an idea of securing images on cloud platform using biometric authentication. Different steps involved in biometric authentication and secure upload and access of images are explained, and integration of all the steps is done at the end as a case study which puts light on the whole process in which methods are best-regarding results and compatibility. The proposed algorithm in this paper presents the idea of authentication of images in two basic steps of image compression using standard discrete wavelet transform method followed by image encryption using the hybrid method of SHA and blowfish. This image is then stored into the database of cloud and accessed whenever the user requests it. A structured and comprehensive view of encryption methods, types of biometrics and to secure data as well as images is provided in this paper.

Biometric authentication and image encryption for image security in cloud framework

A novel quantum image compression and encryption algorithm with Daubechies $$ {D^{(4)}} $$
 quantum wavelet transform (DQWT) and 3D hyper-chaotic Henon map is presented. The quantum image is firstly scrambled by the iterative generalized Arnold transforms to eliminate its block effect. Then, the produced quantum image is compressed with DQWT and measurement matrix, which could be implemented with Hadamard gate. Subsequently, a quantum key image is constructed by a hyper-chaotic Henon sequence generated by 3D hyper-chaotic Henon map under the control of three initial values and two parameters. The quantum key image is XORed with the produced quantum compression image. The key space is relatively large enough since there are three initial values and two parameters involved. Numerical simulations demonstrate that the proposed quantum image compression and encryption algorithm is feasible, secure and efficient.

Novel quantum image compression and encryption algorithm based on DQWT and 3D hyper-chaotic Henon map

In image processing and computer vision, the denoising process is an important step before several processing tasks. This paper presents a new adaptive noise-reducing anisotropic diffusion (ANRAD) method to improve the image quality, which can be considered as a modified version of a speckle-reducing anisotropic diffusion (SRAD) filter. The SRAD works very well for monochrome images with speckle noise. However, in the case of images corrupted with other types of noise, it cannot provide optimal image quality due to the inaccurate noise model. The ANRAD method introduces an automatic RGB noise model estimator in a partial differential equation system similar to the SRAD diffusion, which estimates at each iteration an upper bound of the real noise level function by fitting a lower envelope to the standard deviations of pre-segment image variances. Compared to the conventional SRAD filter, the proposed filter has the advantage of being adapted to the color noise produced by today's CCD digital camera. The simulation results show that the ANRAD filter can reduce the noise while preserving image edges and fine details very well. Also, it is favorably compared to the fast non-local means filter, showing an improvement in the quality of the restored image. A quantitative comparison measure is given by the parameters like the mean structural similarity index and the peak signal-to-noise ratio.

Adaptive noise-reducing anisotropic diffusion filter

Discrete Wavelet Transform, (DWT), is known to be one of the best compression techniques. It provides a mathematical way of encoding information in such a way that it is layered according to level of detail. In this paper, we used Haar wavelets as the basis of transformation functions. Haar wavelet transformation is composed of a sequence of low pass and high pass filters, known as filter bank. The redundancy of the DWT detail coefficients are reduced through thresholding and further through Huffman encoding. The proposed threshold algorithm is based upon the statistics of the DWT coefficients. The quality of the compressed images has been evaluated using some factors like Compression Ratio, (CR), and Peak Signal to Noise Ratio, (PSNR). Experimental results demonstrate that the proposed technique provides sufficient higher compression ratio compared to other compression thresholding techniques.

Image compression based upon Wavelet Transform and a statistical threshold

In recent years, the rapid growth of information technology and digital communication has become very important to secure information transmission between the sender and receiver. Therefore, steganography introduces strongly to hide information and to communicate a secret data in an appropriate multimedia carrier, e.g., image, audio and video files. In this paper, a new algorithm for image steganography has been proposed to hide a large amount of secret data presented by secret color image. This algorithm is based on different size image segmentations (DSIS) and modified least significant bits (MLSB), where the DSIS algorithm has been applied to embed a secret image randomly instead of sequentially; this approach has been applied before embedding process. The number of bit to be replaced at each byte is non uniform, it bases on byte characteristics by constructing an effective hypothesis. The simulation results justify that the proposed approach is employed efficiently and satisfied high imperceptible with high payload capacity reached to four bits per byte.

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A New Image Steganography Algorithm Based on MLSB Method with Random Pixels Selection

Image compression is a key technology in transmission and storage of digital images because of vast data associated with them. This research suggests a new image compression scheme with pruning proposal based on discrete wavelet transformation (DWT). The effectiveness of the algorithm has been justified over some real images, and the performance of the algorithm has been compared with other common compression standards. The algorithm has been implemented using Visual C++ and tested on a Pentium Core 2 Duo 2.1 GHz PC with 1 GB RAM. Experimental results demonstrate that the proposed technique provides sufficient high compression ratios compared to other compression techniques.

/pdf/image-compression-using-discrete-wavelet-transform-4mostx7d8h.pdf

Image Compression Using Discrete Wavelet Transform

Distance Education is a very important instructional delivery for higher education in the 21st century. Along with the rapid development of computer related modern technology such as Internet, videoconferencing, Web conferencing etc., distance education is playing an increasingly important role in schools, colleges and other educational institutes. The advancement of information and communication technology (ICT) has brought revolutionary changes to the mode of distance education. Distance education in the form of E-learning can play a crucial role in broadening access to education for the whole society. The framework of this research focuses on the trends and issues of existing Distance Education in Bangladesh and explores the opportunities as well as the challenges of E-learning to develop a modern distance education system for the disadvantaged people of the country. Considering all issues and challenges this research proposes a model of E-learning assisted distance education system for Bangladesh. This paper also intends to suggest some recommendations for facing the challenges and strengthening infrastructures to implement the system for quality education.

Amina Khatun

Papers

Image Compression Using Discrete Wavelet Transform

Modeling E-Learning Assisted Distance Education System for Bangladesh