Two-stage wireless capsule image compression with low complexity and high quality

Gu, Yingke; Xie, Xiang; Li, Guolin; Sun, Tianjia; Wang, Zhihua

doi:10.1049/el.2012.3470

Cited by 13 publications

(13 citation statements)

References 3 publications

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“…After 3D-DCT, a 4 × 4 × 4 quantization table should be derived by the rate-distortion theory. According to the rate-distortion theory [ 17 , 22 ], the optimization objective function can be expressed by Formula (2).

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Section: The Proposed 3d Dct Compression Methodsmentioning

confidence: 99%

“…In the WCE application, many compression algorithms have been proposed. Generally, they can be classified into two categories, i.e., lossless/near-lossless compression methods [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ], and lossy compression methods [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. In the early research on the compression for this medical application, to assure the quality of medical images, the former methods were generally adopted.…”

Section: Introductionmentioning

confidence: 99%

“…To improve the compression ratio while assuring acceptable image quality (PSNR about 40 dB), lossy compression methods have been discussed in many studies [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Some conventional color-space transformations, such as Y-U-V [ 12 ], Y-Cb-Cr [ 13 ], and Y-Cg-Co [ 14 ], are introduced before discrete cosine transform (DCT) to improve the compression performance, because they can decorrelate the color components to some extent.…”

Section: Introductionmentioning

confidence: 99%

“…However, we found that the KLT based transform is only optimum statistically, instead of being the best transformation for each image or a set of images (e.g., one patient’s endoscopic image set). To reduce the power consumption of the image compression inside the capsule, there are also some works that focus on its low-complexity implementation [ 17 , 18 , 19 ], such as integer DCT followed by a quantization table composed of multiples of 2 [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

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3D DCT Based Image Compression Method for the Medical Endoscopic Application

Xue

Yin

Lan

et al. 2021

Sensors

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This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.

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…”

Section: The Proposed 3d Dct Compression Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3D DCT Based Image Compression Method for the Medical Endoscopic Application

Xue

Yin

Lan

et al. 2021

Sensors

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“…But, these methods allow for some information contained in original images to be lost, resulting in error. There are also a few lossless and high-quality compression methods presented based on structure transformation [5,[12][13][14][15][16][17], but their computation complexity is too high to be adopted in wireless endoscopy application. Moreover, they all belong to multiple-pass compression mechanisms, which are more costly in terms of hardware resources.…”

Section: Introductionmentioning

confidence: 99%

A complexity-efficient and one-pass image compression algorithm for wireless capsule endoscopy

Liu¹,

Yan²,

Zhao³

et al. 2015

THC

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Abstract. BACKGROUND:As an important part of the application-specific integrated circuit (ASIC) in wireless capsule endoscopy (WCE), the efficient compressor is crucial for image transmission and power consumption. OBJECTIVE: In this paper, a complexity-efficient and one-pass image compression method is proposed for WCE with Bayer format images. The algorithm is modified from the standard lossless algorithm (JPEG-LS). METHODS: Firstly, a causal interpolation is used to acquire the context template of a current pixel to be encoded, thus determining different encoding modes. Secondly, a gradient predictor, instead of the median predictor, is designed to improve the accuracy of the predictions. Thirdly, the gradient context is quantized to obtain the context index (Q). Eventually, the encoding process is achieved in different modes. RESULTS: The experimental and comparative results show that our proposed near-lossless compression method provides a high compression rate (2.315) and a high image quality (46.31 dB) compared with other methods. CONCLUSION: It performs well in the designed wireless capsule system and could be applied in other image fields.

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