scispace - formally typeset
Search or ask a question
Topic

Peak signal-to-noise ratio

About: Peak signal-to-noise ratio is a research topic. Over the lifetime, 3294 publications have been published within this topic receiving 23562 citations. The topic is also known as: PSNR.


Papers
More filters
Proceedings ArticleDOI
23 Aug 2010
TL;DR: A simple mathematical relationship is derived between the peak-signal-to-noise ratio and the structural similarity index measure which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and jpeg2000 compression.
Abstract: In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a simple mathematical relationship between them which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and jpeg2000 compression. A series of tests realized on images extracted from the Kodak database gives a better understanding of the similarity and difference between the SSIM and the PSNR.

2,540 citations

Journal ArticleDOI
TL;DR: A modified decision based unsymmetrical trimmed median filter algorithm for the restoration of gray scale, and color images that are highly corrupted by salt and pepper noise is proposed and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).
Abstract: A modified decision based unsymmetrical trimmed median filter algorithm for the restoration of gray scale, and color images that are highly corrupted by salt and pepper noise is proposed in this paper. The proposed algorithm replaces the noisy pixel by trimmed median value when other pixel values, 0's and 255's are present in the selected window and when all the pixel values are 0's and 255's then the noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF). The proposed algorithm is tested against different grayscale and color images and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).

550 citations

Journal ArticleDOI
TL;DR: Comparing different image quality metrics to give a comprehensive view of structural and feature similarity measures between restored and original objects on the basis of perception is mainly stressed.
Abstract: Quality is a very important parameter for all objects and their functionalities. In image-based object recognition, image quality is a prime criterion. For authentic image quality evaluation, ground truth is required. But in practice, it is very difficult to find the ground truth. Usually, image quality is being assessed by full reference metrics, like MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio). In contrast to MSE and PSNR, recently, two more full reference metrics SSIM (Structured Similarity Indexing Method) and FSIM (Feature Similarity Indexing Method) are developed with a view to compare the structural and feature similarity measures between restored and original objects on the basis of perception. This paper is mainly stressed on comparing different image quality metrics to give a comprehensive view. Experimentation with these metrics using benchmark images is performed through denoising for different noise concentrations. All metrics have given consistent results. However, from representation perspective, SSIM and FSIM are normalized, but MSE and PSNR are not; and from semantic perspective, MSE and PSNR are giving only absolute error; on the other hand, SSIM and PSNR are giving perception and saliency-based error. So, SSIM and FSIM can be treated more understandable than the MSE and PSNR.

507 citations

01 Jan 2011
TL;DR: The results have shown that the ATBTC algorithm outperforms the BTC and provides better image quality than image compression using BTC at the same bit rate.
Abstract: The present work investigates image compression using block truncation coding. Two algorithms were selected namely, the original block truncation coding (BTC) and Absolute Moment block truncation coding (AMBTC) and a comparative study was performed. Both of two techniques rely on applying divided image into non overlapping blocks. They differ in the way of selecting the quantization level in order to remove redundancy. Objectives measures were used to evaluate the image quality such as: Peak Signal to Noise Ratio (PSNR), Weighted Peak Signal to Noise Ratio (WPSNR), Bit Rate (BR) and Structural Similarity Index (SSIM).The results have shown that the ATBTC algorithm outperforms the BTC. It has been show that the image compression using AMBTC provides better image quality than image compression using BTC at the same bit rate. Moreover, the AMBTC is quite faster compared to BTC Index Terms—BTC, AMBTC, WPSNR, SSIM.

423 citations

Journal ArticleDOI
TL;DR: This paper proposes an effective color filter array (CFA) interpolation method for digital still cameras (DSCs) using a simple image model that correlates the R,G,B channels and shows that the frequency response of the proposed method is better than the conventional methods.
Abstract: We propose an effective color filter array (CFA) interpolation method for digital still cameras (DSCs) using a simple image model that correlates the R,G,B channels. In this model, we define the constants K/sub R/ as green minus red and K/sub B/ as green minus blue. For real-world images, the contrasts of K/sub R/ and K/sub B/ are quite flat over a small region and this property is suitable for interpolation. The main contribution of this paper is that we propose a low-complexity interpolation method to improve the image quality. We show that the frequency response of the proposed method is better than the conventional methods. Simulation results also verify that the proposed method obtain superior image quality on typical images. The luminance channel of the proposed method outperforms by 6.34-dB peak SNR the bilinear method, and the chrominance channels have a 7.69-dB peak signal-to-noise ratio improvement on average. Furthermore, the complexity of the proposed method is comparable to conventional bilinear interpolation. It requires only add and shift operations to implement.

347 citations


Network Information
Related Topics (5)
Feature extraction
111.8K papers, 2.1M citations
90% related
Wireless sensor network
142K papers, 2.4M citations
85% related
Image processing
229.9K papers, 3.5M citations
85% related
Deep learning
79.8K papers, 2.1M citations
84% related
Artificial neural network
207K papers, 4.5M citations
84% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023108
2022276
2021242
2020219
2019238
2018240