Shading Correction Data Segmentation for Image Sensors
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Solution Overview
Problem
Image reading apparatuses require large volumes of memory to store shading correction data due to the large number of light receiving elements, which can lead to increased memory requirements without compromising image quality.
Innovation Solution
The apparatus includes an image sensor with multiple light receiving elements and a data storage system that uses reduced shading correction data per sensor unit, allowing for image correction based on a smaller number of correcting information pieces than the number of light receiving elements, thereby downsizing memory storage without deteriorating image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If shading correction data is stored for each light receiving element, then image correction quality is improved, but memory volume increases
Solution Approach 1:
The patent divides the image sensor into multiple sensor units, each containing multiple light receiving elements. Instead of storing separate correction data for each individual light receiving element, the system stores one set of correction data per sensor unit. This segmentation approach reduces the total number of correction data sets from N (where N is the total number of light receiving elements) to M (where M is the number of sensor units), directly reducing memory volume while maintaining correction capability at the sensor unit level.
Solution Approach 2:
The patent merges multiple light receiving elements within each sensor unit to share a single set of correction data. By combining the correction requirements of multiple elements into one unified correction dataset per sensor unit, the system achieves memory reduction while preserving sufficient correction quality, as elements within the same sensor unit exhibit similar correction characteristics.
2Productivity
If the number of light receiving elements is increased, then image reading capability is improved, but the number of correction data pieces increases
Solution Approach 1:
By organizing light receiving elements into sensor units and assigning one correction dataset per unit rather than per element, the patent decouples the growth of reading capability (more elements) from the growth of correction data quantity (fewer units). This allows the system to increase image reading capability by adding more light receiving elements without proportionally increasing the number of correction data pieces.
Solution Approach 2:
Each sensor unit's correction dataset serves as a universal correction source for all light receiving elements within that unit. This multi-functional approach allows a single correction dataset to correct multiple elements, reducing the total number of correction data pieces needed while maintaining the ability to read images with a large number of light receiving elements.
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
This approach reduces the memory volume needed for shading correction data while maintaining image reproducibility by using a smaller number of correcting information pieces for each sensor unit, allowing for efficient storage and correction of pixel data.
Implementation Method 1
an image sensor 15, each of which includes a plurality of light receiving elements 19 to receive light and to output pixel data generated according to the received light
Data Source
AI summary
An image reading apparatus to read an image and generate pixel data representing the image is provided. The image reading apparatus includes an image sensor having a plurality of sensor units, each of which includes a plurality of light receiving elements, a data storage store shading correction data, which is used to correct unevenness caused in the pixel data, including first shading correction data, and a data corrector to correct the pixel data output from the light receiving elements based on the shading correction data. The data corrector corrects the pixel data based on the first shading correction data when a number of light receiving elements used to read the image in each sensor unit is greater than a number of pieces of correcting information in the first shading correction data.