scholarly journals ENCRYPTION AND DECRYPTION USING IMAGE PROCESSING TECHNIQUES

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
R.Uma Maheshwari
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Binary Operation ◽  
Speckle Noise ◽  
Discrete Wavelet ◽  
Arnold Transform ◽  
Image Processing Techniques ◽  
Encryption And Decryption ◽  
Processing Techniques

Images consists various kinds of information which can be used for encryption and decryption of messages through them. This paper proposes a photograph encryption and decryption method to encrypt a covert snapshot with the aid of combining the Arnold transform system within the area and decrypting the duvet photograph through combining inverse Arnold become. First, grow to be a cover snapshot into subparts which consists of eight binary pictures with the aid of decimal value to eight-digit binary operation. Then, change into eight binary snap shots into sub-blocks of eight binary scrambled pixel by means of the Arnold change into, respectively. And then, recombine the sequence of the eight binary scrambled matrices right into a scrambled matrix with 256 grey phases in keeping with the special membership. Discrete Wavelet Transform (DWT) is used to perform picture compression on the input picture and secretly hidden photograph which is finished making use of alpha mixing. Sooner or later, derive an encrypted image from the scrambled photograph with the aid of the Hartley turn out to be. Second, decode the encrypted picture making use of inverse Arnold develop. Inverse DWT is performed to regain the compressed pictures. Simulations indicate that the proposed approach has a bigger photograph scrambling measure, more protection and has the robustness against occlusion and speckle noise attacks.

scholarly journals Resolution enrichment of side scan sonar image using wavelet based interpolation methods

2018 ◽  
Vol 7 (2.21) ◽  
pp. 375
Author(s):  
R Kumudham ◽  
S Tarun ◽  
R Avinash ◽  
V Rajendran
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Stationary Wavelet Transform ◽  
Side Scan Sonar ◽  
Image Processing Techniques ◽  
Sonar Image ◽  
Processing Techniques

The resolution of the side scan sonar image which is used to detect on seabed such as mines, ship wrecks, etc is low. This paper helps to utilizes image processing techniques to enhance the resolution and thereby it makes detection and classification of underwater objects accurately. The proposed methods discussed in this paper are Discrete wavelet transform and stationary wavelet transform for enhancing the resolution.  

SOME NOTES ON THE APPLICATION OF DISCRETE WAVELET TRANSFORM IN IMAGE PROCESSING

2011 ◽  
Author(s):  
Egydio C. S. Caria ◽  
Trajano A. de A. Costa ◽  
João Marcos A. Rebello ◽  
Donald O. Thompson ◽  
Dale E. Chimenti
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet

scholarly journals HOUGH TRANSFORM GENERATED STRONG IMAGE HASHING SCHEME FOR COPY DETECTION

2018 ◽  
Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Hough Transform ◽  
Rapid Development ◽  
Discrimination Performance ◽  
Discrete Wavelet ◽  
Image Hashing ◽  
Copy Detection ◽  
Detection Scheme

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   

A Content-Based Watermarking Scheme for Image Authentication Using Discrete Wavelet Transform Inter-Coefficient Relations

2011 ◽  
pp. 173-187
Author(s):  
Latha Parameswaran ◽  
K Anbumani
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Authentication ◽  
Binary String ◽  
Discrete Wavelet ◽  
Host Image ◽  
Relationship Of ◽  
Watermarking Scheme ◽  
Authentication Technique

This chapter discusses a content-based authentication technique based on inter-coefficient relationship of Discrete Wavelet Transform (DWT). Watermark is generated from the first level DWT. An image digest (which is a binary string) is generated from the second level DWT. The watermark is embedded in the mid-frequency coefficients of first level DWT as directed by the image digest. Image authentication is done by computing the Completeness of Signature. The proposed scheme is capable of withstanding incidental image processing operations such as compression and identifies any malicious tampering done on the host image.

scholarly journals Analysis of the Quantization Noise in Discrete Wavelet Transform Filters for Image Processing

Electronics ◽  
2018 ◽  
Vol 7 (8) ◽  
pp. 135 ◽  
Author(s):  
Nikolay Chervyakov ◽  
Pavel Lyakhov ◽  
Dmitry Kaplun ◽  
Denis Butusov ◽  
Nikolay Nagornov
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Integrated Circuit ◽  
Filter Banks ◽  
Signal To Noise Ratio ◽  
Quantization Noise ◽  
Discrete Wavelet ◽  
Field Programmable ◽  
Application Specific Integrated Circuit

In this paper, we analyze the noise quantization effects in coefficients of discrete wavelet transform (DWT) filter banks for image processing. We propose the implementation of the DWT method, making it possible to determine the effective bit-width of the filter banks coefficients at which the quantization noise does not significantly affect the image processing results according to the peak signal-to-noise ratio (PSNR). The dependence between the PSNR of the DWT image quality on the wavelet and the bit-width of the wavelet filter coefficients is analyzed. The formulas for determining the minimal bit-width of the filter coefficients at which the processed image achieves high quality (PSNR ≥ 40 dB) are given. The obtained theoretical results were confirmed through the simulation of DWT for a test image using the calculated bit-width values. All considered algorithms operate with fixed-point numbers, which simplifies their hardware implementation on modern devices: field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), etc.

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