A Reduced Reference Distortion Measure for Performance Improvement of Smart Cameras

Abstract

Application specific information processing (ASIP) unit in smart cameras requires sophisticated image processing algorithms for image quality improvement and extraction of relevant features for image understanding and machine vision. The improvement in performance as well as robustness can be achieved by intelligent moderation of the parameters both at algorithm (image resolution, contrast, compression, and so on) as well as hardware levels (camera orientation, field of view, and so on). This paper discusses the employment of ISO/IEC/IEEE 21451 smart transducer standards for performance improvement of smart cameras. The standardized transducer electronic data sheets (TEDS-by IEEE 21450) provide the self description of sensors, of which the calibration details are of vital importance to yield a smart and reconfigurable imaging system. This is possible by exercising intelligent control over the TEDS (smart camera) calibration details as well as automated tuning of algorithm parameters (in ASIP) based on decisions by perceptually efficient image quality assessment (IQA) tool. Estimation of distortion based on reduced reference IQA has been highlighted as a reliable methodology for this purpose. The proposed IQA approach uses wavelets for features extraction followed by estimation of luminance, contrast, and divergence parameters to obtain the proposed distortion measure (Q). The computational complexity in the process has been catalyzed using integral image and gradient magnitude approaches. The validation of Q metric is carried out by evaluating the image quality for various types of distortions on images from Content-based Strategies of Image Quality assessment (CSIQ) and Information Visualization CyberInfrastructure (IVC) databases. Simulation results yield a healthy correlation of Q and the subjective human opinions.


Autore Pugliese

Tutti gli autori

  • Bhateja V. , Kalsi A. , Srivastava A. , Lay-Ekuakille A.

Titolo volume/Rivista

IEEE SENSORS JOURNAL


Anno di pubblicazione

2015

ISSN

1530-437X

ISBN

Non Disponibile


Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile


Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

28/04/2018


Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile