Novel chroma subsampling patterns for wireless capsule endoscopy compression

Babu, C. Nelson Kennedy; Chandy, D. Abraham; Karthigaikumar, P.

doi:10.1007/s00521-019-04143-7

Cited by 8 publications

(3 citation statements)

References 25 publications

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“…The chrominance-based color spaces prove to be effective in reducing the representation and achieves data reduction [5]. The YUV model is preferred for the compression scenario as the variation of the component values in YUV representation is less compared to the RGB model [15]. The RGB to YUV conversion is present in some capsules and the process is reversible.…”

Section: A Pre-processingmentioning

confidence: 99%

“…Literature shows that Golomb coders are most preferred as stage 2 coders for WCE due to its ease for hardware implementation [21]. The prediction error is mapped to positive values and applied to the Golomb coder details as discussed in our previous work [22]. The resulting bitstream is a sequence of zeros and ones which are then transmitted wirelessly to the receiver end through the channel.…”

Section: Golomb Rice Codermentioning

confidence: 99%

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Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression

Babu*,

Chandy*

2020

IJRTE

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Wireless capsule endoscopy is a medical diagnostic technique developed for the endoscopic examination of the small bowel. The encoder module is the core of the wireless capsule endoscopic system impacting on power and area requirement for the hardware implementation of the capsule. One of the remarkable features of the endoscopic image is that the neighboring pixels are highly correlated. Two predictive coding techniques are considered in this work exploiting the above fact. The first predictive coder i.e., DPCM coder is based on previous horizontal neighboring pixel, whereas the second predictive coder is based on adjacent horizontal and diagonal neighbors. The performance of the predictive coders is tested with 41 small bowel type endoscopic images available in the Gastrolab dataset. The results show that the average compression rate and peak signal to noise ratio attained by DPCM coder and newly tested predictive coder are 66.37 % & 73.03 % and 32.17 dB & 35.55 dB, respectively

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Section: A Pre-processingmentioning

confidence: 99%

Section: Golomb Rice Codermentioning

confidence: 99%

Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression

Babu*,

Chandy*

2020

IJRTE

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“…Second, the sharp transition boundary between the corner regions (non-informative regions) and circular visual region of the endoscopic capsule image is highly affected by lossy image compression algorithms that involve sub-sampling and quantization such as DCT-based [15] and DWT-based [16] algorithms. Similarly, the quantization and subsampling operation in DPCM-based [17], [18], and error due to inadequate side information in distributed video coding algorithms [19]. However, this region has no significant information relevant to the diagnosis of abnormalities in the gastrointestinal tract.…”

Section: Introductionmentioning

confidence: 99%

An Ingenious Application-Specific Quality Assessment Methods for Compressed Wireless Capsule Endoscopy Images

Fante

Abdurahman

Gemeda

2020

TEEE

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<pre>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 general-purpose 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 application. The proposed objective IQA methods are obtained by modifying the existing full-reference image quality assessment techniques. The modification is done by excluding the non-informative regions, in endoscopic images, in the computation of IQA metrics. The experimental results demonstrate that the proposed IQA method gives an improvement of 2.12 dB peak signal-to-noise ratio (PSNR) and improved structural similarity index (SSIM). The proposed method gives more reliable objective image quality measures for compressed endoscopic capsule images.</pre>

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Investigation of PCA as a compression pre-processing tool for X-ray image classification

Doorsamy

Rameshar

2021

Neural Comput & Applic

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Novel chroma subsampling patterns for wireless capsule endoscopy compression

Cited by 8 publications

References 25 publications

Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression

Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression

An Ingenious Application-Specific Quality Assessment Methods for Compressed Wireless Capsule Endoscopy Images

Investigation of PCA as a compression pre-processing tool for X-ray image classification

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