Audio Compression Algorithm using Discrete Cosine Transform (DCT) and Lempel-Ziv-Welch (LZW) Encoding Method

2019 ◽  
Author(s):  
Sankalp Shukla ◽  
Maniram Ahirwar ◽  
Ritu Gupta ◽  
Sarthak Jain ◽  
Dheeraj Singh Rajput
Keyword(s):  
Discrete Cosine Transform ◽  
Compression Algorithm ◽  
Audio Compression ◽  
Cosine Transform ◽  
Encoding Method

Approximate Constant-Coefficient Multiplication Using Hybrid Binary-Unary Computing for FPGAs

2022 ◽  
Vol 15 (3) ◽  
pp. 1-25
Author(s):  
S. Rasoul Faraji ◽  
Pierre Abillama ◽  
Kia Bazargan
Keyword(s):  
Discrete Cosine Transform ◽  
Video Processing ◽  
High Speed ◽  
Low Cost ◽  
Digital Signal ◽  
Logic Gates ◽  
Cosine Transform ◽  
Real Time Processing ◽  
Coefficient Multiplier ◽  
Encoding Method

Multipliers are used in virtually all Digital Signal Processing (DSP) applications such as image and video processing. Multiplier efficiency has a direct impact on the overall performance of such applications, especially when real-time processing is needed, as in 4K video processing, or where hardware resources are limited, as in mobile and IoT devices. We propose a novel, low-cost, low energy, and high-speed approximate constant coefficient multiplier (CCM) using a hybrid binary-unary encoding method. The proposed method implements a CCM using simple routing networks with no logic gates in the unary domain, which results in more efficient multipliers compared to Xilinx LogiCORE IP CCMs and table-based KCM CCMs (Flopoco) on average. We evaluate the proposed multipliers on 2-D discrete cosine transform algorithm as a common DSP module. Post-routing FPGA results show that the proposed multipliers can improve the {area, area × delay, power consumption, and energy-delay product} of a 2-D discrete cosine transform on average by {30%, 33%, 30%, 31%}. Moreover, the throughput of the proposed 2-D discrete cosine transform is on average 5% more than that of the binary architecture implemented using table-based KCM CCMs. We will show that our method has fewer routability issues compared to binary implementations when implementing a DCT core.

scholarly journals Estimating Previous Quantization Factors on Multiple JPEG Compressed Images

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sebastiano Battiato ◽  
Oliver Giudice ◽  
Francesco Guarnera ◽  
Giovanni Puglisi
Keyword(s):  
Image Quality ◽  
Discrete Cosine Transform ◽  
Jpeg Compression ◽  
Compression Algorithm ◽  
Experimental Results ◽  
The Other ◽  
Cosine Transform ◽  
Novel Technique ◽  
Compressed Images ◽  
Acquisition Device

AbstractThe JPEG compression algorithm has proven to be efficient in saving storage and preserving image quality thus becoming extremely popular. On the other hand, the overall process leaves traces into encoded signals which are typically exploited for forensic purposes: for instance, the compression parameters of the acquisition device (or editing software) could be inferred. To this aim, in this paper a novel technique to estimate “previous” JPEG quantization factors on images compressed multiple times, in the aligned case by analyzing statistical traces hidden on Discrete Cosine Transform (DCT) histograms is exploited. Experimental results on double, triple and quadruple compressed images, demonstrate the effectiveness of the proposed technique while unveiling further interesting insights.

LWT-DCT based Image Watermarking Scheme using Normalized SVD

2020 ◽  
Vol 13 ◽  
Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Cosine Transform ◽  
Image Watermarking ◽  
Singular Value ◽  
Cover Image ◽  
Lifting Wavelet Transform ◽  
Cosine Transform ◽  
Lifting Wavelet ◽  
Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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