Inkjet Image Processing Reducing Density Unevenness Without Granularity
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Solution Overview
Problem
Existing image processing methods for ink jet printing fail to effectively reduce density unevenness caused by nozzle ejection characteristic variations without worsening image granularity, as they either interfere with dither matrices or cannot reduce dot size, leading to increased granularity.
Innovation Solution
An image processing apparatus and method that uses a combination of common and per-nozzle correction tables, followed by quantization, to generate N-valued print data, allowing for density correction across multiple nozzles while maintaining dot arrangement specified by the dither matrix, thereby reducing density unevenness without worsening granularity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If correction is performed for image data using per-nozzle correction tables, then density unevenness is reduced, but dot concentration varies causing granularity
Solution Approach 1:
The correction process is divided into two independent segmentation steps: first correcting image data using a common correction table, then quantizing to determine dot arrangement, and finally correcting using per-nozzle correction tables. This segmentation ensures that dot arrangement is fixed before per-nozzle corrections are applied, preventing granularity while achieving density uniformity.
Solution Approach 2:
The common correction and quantization processes are performed as preliminary actions before per-nozzle correction. By establishing the dot arrangement through quantization first, the subsequent per-nozzle correction operates on fixed dot positions, avoiding any interference with the dither matrix and preventing granularity formation.
2Measurement precision
If correction is performed after quantization, then dither matrix interference is avoided, but dot size cannot be reduced leading to increased granularity
Solution Approach 1:
The solution adds a new dimension to the correction process by introducing per-nozzle correction tables that operate in the density value domain after quantization. This allows correction of density variations without altering dot positions or sizes, achieving density uniformity while preserving the quantization results and avoiding granularity.
3Device complexity
If common correction table is used, then processing is simplified, but per-nozzle density variations cannot be corrected
Solution Approach 1:
The solution merges two correction approaches: common correction tables that handle overall density characteristics and per-nozzle correction tables that handle nozzle-specific variations. By combining these two correction mechanisms in sequence, the system achieves both simplified processing (through common correction) and precise per-nozzle uniformity (through individual correction tables).
Data Source
AI summary
Density unevenness accompanying a variation in an ejection characteristic of each nozzle is reduced without worsening granularity of an image. To this end, an image processing apparatus generates first corrected data by correcting image data by using a first correction table common to the plurality of nozzles. Further, the image processing apparatus generates second corrected data by correcting the image data by using a second correction table for each of the plurality of nozzles. Furthermore, the image processing apparatus generates first quantized data by quantizing the first corrected data and generates second quantized data by quantizing the second corrected data. After that, the image processing apparatus generates N-valued print data based on the first quantized data and the second quantized data.