Image Processing for Wireless Capsule Endoscopy
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Solution Overview
Problem
Conventional image processing techniques for wireless capsule endoscopy are inefficient in terms of size, power consumption, and image quality, particularly due to the need for large buffer memories and complex computational operations, which hinder the ability to maintain high image resolution and frame rates while ensuring accurate medical diagnosis.
Innovation Solution
The method involves processing images using a color image sensor by generating a luma channel and chroma channels, applying lossless predictive coding, and variable length coding, which reduces complexity and power consumption, enabling efficient image compression and transmission while maintaining sufficient image quality for medical diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing techniques are used in wireless capsule endoscopy, then image quality can be maintained, but device size and power consumption increase significantly
Solution Approach 1:
The patent divides the image processing into separate functional stages: color space conversion (RGB to YUV), predictive coding, and variable length coding. Each stage processes specific aspects of the image data independently, allowing optimized processing for each function while reducing overall computational burden on the capsule device.
Solution Approach 2:
The patent transforms the color space from RGB to YUV, changing the parameter representation of color information. This parameter transformation enables more efficient compression by separating luminance (Y) from chrominance (UV) components, allowing lower bit rates while maintaining acceptable image quality for diagnostic purposes.
2Measurement precision
If conventional image processing techniques are used in wireless capsule endoscopy, then image quality can be maintained, but device size increases due to large buffer memories
Solution Approach 1:
The patent performs color space conversion and predictive coding operations on image data as it is captured and processed immediately, rather than buffering large portions of raw image data in memory. This preliminary processing reduces the amount of data that needs to be stored, thereby reducing the required buffer memory size in the capsule device.
Solution Approach 2:
The patent extracts and processes only the essential information from the captured images through predictive coding and variable length coding, discarding redundant information. This extraction approach reduces the data volume that must be buffered and transmitted, minimizing the required device memory and storage capacity.
3Measurement precision
If complex computational operations are used in image processing, then image quality and processing accuracy improve, but power consumption and computational complexity increase
Solution Approach 1:
The patent replaces complex computational operations with more efficient algorithms. Specifically, it uses predictive coding that leverages temporal and spatial correlations in the image data, substituting heavy mathematical computations with simpler predictive models that achieve comparable or superior compression efficiency with reduced computational complexity.
Solution Approach 2:
The patent applies variable length coding that assigns shorter codes to more frequent symbols and longer codes to less frequent symbols. This partial optimization approach focuses computational effort on the most significant data elements first, achieving good compression ratios without requiring complex processing of all data uniformly, thereby reducing overall computational complexity.
4Productivity
If high frame rates and image resolution are maintained, then diagnostic accuracy improves, but power consumption and data transmission requirements increase
Solution Approach 1:
The patent changes the parameter representation of image data through color space conversion and predictive coding, reducing the number of bits required to represent each frame. This parameter transformation enables the transmission of high frame rate images at lower data rates, reducing power consumption for both processing and wireless transmission while maintaining diagnostic quality.
Data Source
AI summary
Methods and apparatus for image processing suitable for use in wireless capsule endoscopy are provided. The image processing techniques exploit characteristic features of endoscopic images to enable low complexity compression. A color space conversion, coupled with lossless predictive coding and variable length coding are employed. Sub-sampling and clipping may also be used. The described image processing can be used both with both white-band imaging and narrow-band-imaging.