Monochromatic Sensor Colorization via Sequential Multicolor Illumination
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Solution Overview
Problem
Existing imaging methods using monochromatic sensors face challenges in accurately visualizing target treatment sites within a patient, such as tumors or lesions in the gastrointestinal tract, due to limitations in colorizing images, which overburden image processors and cause processing delays.
Innovation Solution
A method involving sequential illumination of a surface with multiple colors, capturing multiple image frames, normalizing color intensities, and determining a correlation score to generate a color image using monochromatic sensors, along with a medical device equipped with a monochromatic image sensor and illumination devices to perform image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional colorization methods are used on monochromatic images, then color information can be added to target sites, but image processors become overburdened and processing delays occur
Solution Approach 1:
The system performs preliminary action by capturing multiple spectral images at different wavelengths before the final colorization processing. The monochromatic sensor captures images at multiple discrete wavelengths (e.g., UV, visible, NIR) in sequence, storing this spectral data for later reconstruction. This preliminary capture of multi-wavelength data reduces the computational burden during final colorization, as the spectral information is already acquired and organized, allowing faster processing compared to attempting to derive all color information from a single monochromatic image.
2Measurement precision
If multiple spectral images are captured and processed, then accurate colorization is achieved, but processing time increases
Solution Approach 1:
The system applies segmentation by dividing the spectral imaging process into discrete wavelength bands (e.g., UV at 365nm, visible at 450-650nm, NIR at 780-940nm). Each wavelength band is captured separately by the monochromatic sensor, allowing independent optimization of exposure and illumination for each spectral region. This segmentation enables selective processing where only relevant spectral bands are fully processed, while others may be processed at reduced fidelity, thereby maintaining color accuracy for diagnostic features while reducing overall processing time.
Solution Approach 2:
The system utilizes parameter changes by varying the illumination wavelength and sensor spectral response across multiple discrete wavelengths. The monochromatic sensor's spectral sensitivity is leveraged by changing the illumination source wavelength (e.g., using LED arrays with different peak wavelengths) to capture images at specific spectral points. This parameter variation allows the system to optimize the balance between color information capture and processing load, as fewer discrete wavelength samples are required compared to continuous spectral scanning, thus reducing processing time while maintaining sufficient color accuracy for medical visualization.
3Reliability
If monochromatic sensors are used, then spectral flexibility and contrast definition are improved, but color visualization capability is limited
Solution Approach 1:
The system introduces an intermediary computational process that acts as a mediator between the monochromatic sensor data and the desired color output. Instead of relying on the sensor to directly capture color information, the system uses the monochromatic images captured at multiple discrete wavelengths as intermediaries. These intermediate monochromatic images are then processed through spectral unmixing and color reconstruction algorithms that synthesize the perceived color information based on the spectral reflectance characteristics of the tissue. This intermediary approach allows the monochromatic sensor to maintain its advantages in contrast and spectral flexibility while still enabling color visualization through computational reconstruction.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and accurate colorization of images captured by monochromatic sensors, reducing processing delays and improving visualization of target sites within the gastrointestinal tract.
Implementation Method 1
Each of the plurality of illumination devices is configured to emit a different color of light
Implementation Method 2
A monochromatic image sensor may be used to capture images of the target site
Data Source
AI summary
A method of generating a color image using a monochromatic image sensor. The method includes sequentially illuminating a surface in a plurality of colors, one color at a time. The monochromatic image sensor captures a plurality of image frames of the surface based on the plurality of colors. The plurality of image frames are identified, and at least one feature in the target of the plurality of image frames is highlighted. Color intensities of the plurality of image frames are normalized. A color intensity map of the target for each of the plurality of image frames is generated. A correlation score is determined by comparing each color intensity map of the plurality of image frames. The color image is generated based on the correlation score.