Image Resolution Conversion Using Pixel Tag Data
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Solution Overview
Problem
Existing image forming apparatuses face challenges in efficiently converting low-resolution image data into high-resolution data without increasing data transmission, leading to potential image blurring or loss of detail, particularly in forming small text or line images.
Innovation Solution
The apparatus employs a circuitry system that receives first image data and tag data, identifies specific target pixels, and converts them into second image data with higher resolution, using tag data to control a light source for precise pixel pattern generation, thereby enhancing image resolution without increasing data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image data is converted from low resolution to high resolution, then image quality and detail are improved, but data transmission amount increases
Solution Approach 1:
The patent applies local quality by differentiating processing based on pixel attributes. Only specific pixels identified as target pixels through tag data analysis undergo resolution enhancement conversion, while other pixels maintain their original resolution. This selective approach improves image quality where needed without unnecessarily increasing overall data transmission.
Solution Approach 2:
The image data is segmented into different categories based on pixel attributes indicated by tag data. The system divides pixels into target pixels requiring resolution enhancement and non-target pixels that maintain original resolution, allowing differential processing that balances quality improvement with data efficiency.
2Manufacturing precision
If all pixels are converted to high resolution, then image detail is improved, but processing time and complexity increase
Solution Approach 1:
The patent implements partial action by converting only a subset of pixels (target pixels identified through tag data) to high resolution rather than all pixels. This selective conversion achieves sufficient image detail for small text and line images while significantly reducing processing time and computational complexity compared to full-image conversion.
Solution Approach 2:
Different processing quality is applied to different regions/pixels based on their attributes. Target pixels undergo high-resolution conversion to preserve detail, while other pixels maintain lower resolution, optimizing the balance between processing speed and image quality.
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 allows for the formation of high-quality images with improved resolution and reduced blurring, particularly in small text or line images, by thickening pixels to maintain image clarity and detail.
Implementation Method 1
An optical scanner irradiates the surface of the photoconductor thus charged with a light beam to form an electrostatic latent image on the surface of the photoconductor according to the image data
Data Source
AI summary
An image forming apparatus includes a photoconductor, a light source, and circuitry that receives: first image data including first pixels each indicating image density or one of turning on and off the light source; and tag data indicating an attribute of each first pixels. The circuitry sets specific data to identify a first target pixel subjected to change out of the first pixels, converts the first image data into second image data having a higher resolution than that of the first image data, and controls the light source according to the second image data to form an image. In conversion, the circuitry identifies a second target pixel corresponding to the first target pixel out of second pixels of the second image data according to the specific data and the tag data, and changes the second target pixel into a pixel to turn on the light source.