Image Processing Apparatus Using Lookup Table for Super-Resolution
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Solution Overview
Problem
Existing image processing technologies face challenges in achieving high-accuracy resolution interpolation at high speeds due to incomplete specification of camera models and alignment, leading to issues like overemphasis of edges, noise emphasis, and increased processing loads.
Innovation Solution
An image processing apparatus and method that incorporates a model-based processing unit for converting resolution based on a camera model and alignment, along with a prediction operation unit using parameters stored in a learning database to enhance pixel value prediction, including motion compensation, blur addition and removal, and class sorting for improved image interpolation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If repeated operations are performed for super-resolution processing, then manufacturing precision of the high-resolution image is improved, but productivity deteriorates due to large processing load
Solution Approach 1:
The patent pre-calculates and stores correction values in a lookup table before actual super-resolution processing. During processing, the system simply retrieves pre-computed values based on motion vectors and pixel positions, avoiding repeated complex calculations. This preliminary preparation enables fast real-time processing while maintaining high image quality through accurate correction values.
2Manufacturing precision
If camera model and aligning are accurately specified, then manufacturing precision of the high-resolution image is improved, but device complexity increases
Solution Approach 1:
The patent introduces a lookup table as an intermediary structure that stores pre-computed correction values. Instead of directly implementing complex camera models and alignment calculations during processing, the system uses motion vectors to index into the lookup table and retrieve appropriate correction values. This intermediary approach simplifies the processing architecture while maintaining accurate correction based on sophisticated camera models.
3Reliability
If reconstruction-type super-resolution MAP method is used to prevent noise emphasis, then reliability of image quality is improved, but manufacturing precision deteriorates due to dependence on advance information
Solution Approach 1:
The patent incorporates feedback mechanisms where correction values are computed based on actual motion vectors obtained from the input images. The system uses the observed low-resolution images to determine motion, then retrieves or computes correction values that are specifically tailored to the actual motion present. This feedback loop ensures that noise suppression and resolution enhancement are adapted to the specific input conditions, maintaining both reliability and precision.
Data Source
AI summary
There is provided an image processing apparatus including a model-based processing unit that executes model-based processing for converting resolution and converting an image on the basis of a camera model and a predetermined model having aligning, with respect to a high-resolution image output one frame before, and a prediction operation unit that performs a prediction operation on a pixel value of a high-resolution image to be output, on the basis of parameters stored in advance, an observed low-resolution image that is an input low-resolution image, and an image obtained by executing the model-based processing.