Abstract
<p>Image quality assessment methods are used in different image processing applications. Among them, image compression and image super-resolution can be mentioned in wireless capsule endoscopy (WCE) applications. The existing image compression algorithms for WCE employ the generalpurpose image quality assessment (IQA) methods to evaluate the quality of the compressed image. Due to the specific nature of the images captured by WCE, the general-purpose IQA methods are not optimal and give less correlated results to that of subjective IQA (visual perception). This paper presents improved image quality assessment techniques for wireless capsule endoscopy applications. The proposed objective IQA methods are obtained by modifying the existing full-reference image quality assessment techniques. The modification is done by excluding the noninformative regions, in endoscopic images, in the computation of IQA metrics. The experimental results demonstrate that the proposed IQA method gives an improved peak signal-tonoise ratio (PSNR) and structural similarity index (SSIM). The proposed image quality assessment methods are more reliable for compressed endoscopic capsule images.</p>
Highlights
Wireless capsule endoscopy (WCE) is a tablet size camera with a radio frequency transmitter which can be ingested by patients to diagnose gastrointestinal abnormalities [1]
The two selected image quality assessment (IQA) methods used in this work for demonstration purposes are peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM)
This leads to IQA metrics, which has less correlation with the subjective image quality assessment method
Summary
Wireless capsule endoscopy (WCE) is a tablet size camera with a radio frequency transmitter which can be ingested by patients to diagnose gastrointestinal abnormalities [1]. It enables the non-invasive imaging of the gastrointestinal tract with a high-resolution camera operating in the visible electromagnetic spectrum. The transmission of high-resolution images via a wireless link consumes high power and requires a high transmission bandwidth [2]. In order to reduce the power consumption and transmission bandwidth, image compression algorithms are included inside the capsule [3]. Among the image processing methods, super-resolution algorithms [4] are proposed to improve the spatial resolution of the images, image post-processing and error-correcting codes are proposed to suppress the distortion due to transmission channel noise [5], and computer-aided diagnosis systems [6] are used to improve the detection of abnormalities during the evaluation phase
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