Image Quantization Using Dynamic Range Mapping
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Solution Overview
Problem
Existing image processing methods for commercial and industrial printing face challenges in efficiently quantizing signal values to low bits without deteriorating image quality, particularly when dealing with wide color gamuts, as they often require complex processing and may result in reduced gradations and image details.
Innovation Solution
An image processing apparatus that acquires image data, determines data range information for each color component, and uses one-dimensional lookup tables (LUTs) to quantize signal values from high bits to low bits, ensuring the maximum and minimum values align with the new bit range, thereby maintaining the number of gradations and simplifying the quantization process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If signal values are quantized to low bits for data compression, then data transmission efficiency is improved, but image quality deteriorates due to loss of gradation information
Solution Approach 1:
The patent changes the quantization parameters dynamically based on the actual data range (minimum and maximum signal values) of the image. Instead of using fixed quantization intervals, the system calculates optimal quantization steps that adapt to the specific image characteristics, allowing efficient compression while preserving essential image quality.
Solution Approach 2:
The patent performs preliminary analysis of the image data to determine the minimum and maximum signal values before quantization. This preliminary action allows the system to pre-calculate the optimal quantization parameters and mapping relationships, ensuring that the quantization process preserves image quality without requiring complex real-time processing during transmission.
2Manufacturing precision
If complex quantization processing is used to maintain image quality, then image quality is preserved, but processing complexity increases
Solution Approach 1:
The patent segments the quantization process into distinct stages: (1) determining minimum and maximum signal values, (2) calculating quantization parameters based on these values, (3) applying the quantization mapping. This segmentation simplifies the overall complexity by breaking down the complex quantization task into manageable, sequential steps that can be implemented efficiently.
Solution Approach 2:
The patent changes the quantization parameters based on the actual data range of the input image. By calculating the minimum and maximum values and adjusting the quantization intervals accordingly, the system achieves high-quality compression with a relatively simple processing algorithm that adapts to different image characteristics without requiring complex fixed-structure processing.
3Ease of operation
If fixed quantization intervals are used for simplicity, then processing is simplified, but image quality deteriorates due to inappropriate mapping
Solution Approach 1:
The patent introduces dynamic quantization intervals that adapt to the specific image data range. Instead of using fixed quantization steps, the system calculates quantization parameters that are specific to each image's minimum and maximum values. This dynamic approach maintains processing simplicity while significantly improving image quality by ensuring appropriate mapping for each image.
Solution Approach 2:
The patent changes the quantization parameters (intervals and mapping relationships) based on the actual minimum and maximum signal values of the input image. This parameter adaptation allows the system to maintain simple processing logic while achieving optimal image quality for each specific image, avoiding the quality loss associated with fixed quantization intervals.
Data Source
AI summary
An image processing apparatus acquiring image data whose color information is defined by N-bit signal values; acquiring data range information; quantizing the signal values for each of the color components in the acquired image data into M-bit signal values (N>M) based on the data range information; and a transmitting unit configured to transmit the quantized image data, wherein the quantizing is performed so that the maximum value of the signal values for each of the color components in the acquired image data becomes a maximum possible value in the range of the M bits, and the minimum value of the signal values for each of the color components in the acquired image data becomes a minimum possible value in the range of the M bits.