Real-Time FPGA Integration for Image Steganography Using Haar wavelet and Least Significant Bit Technique | Chapter 2 | Scientific Research, New Technologies and Applications Vol. 6

 

The purpose of this study is to develop a robust image steganography system that enhances the security of hidden communications by employing the Least Significant Bit (LSB) and Discrete Wavelet Transform (DWT) methods. The research aims to improve the robustness of the steganographic process and evaluate the effectiveness of these techniques. The study implements image steganography using two techniques: the Least Significant Bit (LSB) method and the Discrete Wavelet Transform (DWT) method. The performance of these algorithms is evaluated using key metrics such as Mean Squared Error (MSE), Bit Error Rate (BER), Peak Signal-to-Noise Ratio (PSNR), and processing time. The LSB method achieved PSNR values ranging from 42 to 46 dB and MSE values between 1.5 and 3.5. In contrast, the DWT method demonstrated superior performance, with PSNR values ranging from 49 to 57 dB and MSE values from 0.2 to 0.7. These results indicate that the DWT method provides higher performance and robustness compared to the LSB technique. The Discrete Wavelet Transform (DWT) method outperforms the Least Significant Bit (LSB) technique, offering better PSNR and lower MSE values. This makes DWT a more robust and efficient solution for image steganography, particularly in scenarios requiring high security and minimal image distortion.

 

 

Author(s) Details

Mangal Patil

Department of ECE, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

Shankar Madkar

Department of ECE, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

Jyoti Morbale

Department of ECE, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

Harshal Hemane

Department of ECE, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/srnta/v6/2197

 

A Novel Image Reconstruction Approach on Thoracic SPECT Images for Instant and Accurate Response | Chapter 8 | New Visions in Medicine and Medical Science Vol. 3

 Single-photon emission Computed Tomography (SPECT) is an emission imaging modality based on the administration of radiopharmaceuticals to patients. In Single-Photon Emission Computed Tomography (SPECT), the reconstructed image often suffers from insufficient contrast, poor resolution, and inaccurate volume of the tumor size due to physical degradation factors. Generally, nonstationary filtering of the projection or the slice is employed as one of the strategies for correcting the resolution and improving the quality of the reconstructed SPECT images. This chapter presents a new 3D algorithm aimed at enhancing the quality of reconstructed thoracic SPECT images and reducing the noise level with the highest degree of accuracy. Two classes of the analytic algorithm are developed: simple back-projection (SBP) and filtered back-projection (FBP). The suggested algorithm comprises three steps. The first one involves denoising the acquired projections using the benefits of the complementary properties of both the Curvelet transform and the Wavelet transforms to achieve optimal noise reduction. The second step involves the simultaneous reconstruction of the axial slices using the 3D Ordered Subset Expectation Maximization (OSEM) algorithm. The last step involves post-processing the reconstructed axial slices using one of the newest anisotropic diffusion models named Partial Differential Equation (PDE). The method is tested on two digital phantoms and clinical bone SPECT images. A comparative study with four algorithms reviewed in the state of the art proves the significance of the proposed method. In simulated data, experimental results show that the plot profile of the proposed model closely approximates the original one compared to the other algorithms. Furthermore, it presents a notable gain in terms of contrast to noise ratio (CNR) and execution time. The proposed model shows better results in the computation of the contrast metric with a value of 0.68±7.2 and the highest signal-to-noise ratio (SNR) with a value of 78.56±6.4 in real data. The experimental results prove that the proposed algorithm is more accurate and robust in reconstructing SPECT images than the other algorithms. It could be considered a valuable candidate for correcting the resolution of bone in SPECT images. Future research may focus on combining this algorithm with a deep learning method to obtain an optimal and innovative method of bone SPECT image reconstruction.

Author(s) Details:

Afef Houimli,
University of Tunis El Manar, Higher Institute of Medical Technologies of Tunis, Research Laboratory in Biophysics and Medical Technologies LR13ES07, Tunis, 1006, Tunisia.

Issam Ben Mhamed,
Higher National School of Engineers of Tunis, University of Tunis, Signal Image and Energy Management Laboratory: SIME ES03 SIME, ENSIT, Montfleury, 1008, Tunisia.

Dorra Ben-Sellem,
University of Tunis El Manar, Higher Institute of Medical Technologies of Tunis, Research Laboratory in Biophysics and Medical Technologies LR13ES07, Tunis, 1006, Tunisia, Faculty of Medicine of Tunis, University of Tunis El Manar, 1007, Tunisia and Nuclear Medicine Department, Salah AZAIEZ Institute, Tunis, 1006, Tunisia.

Please see the link here: https://stm.bookpi.org/NVMMS-V3/article/view/13956

Determination of FPGA Implementation of New LM-SPIHT Colored Image Compression with Reduced Complexity and Low Memory Requirement Compatible for 5G | Chapter 2 | New Approaches in Engineering Research Vol. 10

 The development of 5G mobile networks needs a change in image processing. These alterations are represented by the needed processing time as well as the amount of space for uploading and downloading. This paper proposes an image compression approach based on WT (Wavelet Transform), LM-SPIHT (Listless-Modified Set Partitioning in Hierarchical Tree) coding, and a second level of Runlength encoding. Both grayscale and coloured images can be processed using the SPIHT method. SPIHT has outstanding qualities in various areas, including image quality, coding and decoding speed, and a completely progressive bit stream. Lossless compression, error prevention, and the ability to code for exact bit rate are all applications. The new implementation attempts to reduce the amount of data that needs to be saved in various stages, as well as the amount of time it takes to process the data. The compression was implemented on the netFPGA-1G-CLM Kintex-7 board using VHDL (Very High Descriptive Language). The new approach was successful in decreasing the compression system's complexity while also cutting processing time.

Author (S) Details

Yasmine M. Tabra
Department of Information & Communication, Information Engineering College, Al-Nahrain University, Iraq.

Bayan Mahdi Sabbar
Department of Information & Communication, Information Engineering College, Al-Nahrain University, Iraq.

View Book :- https://stm.bookpi.org/NAER-V10/article/view/2978