High Resolution Image Reconstruction via Characteristic Data Extraction
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Solution Overview
Problem
Existing electronic systems lack an efficient method to generate high-resolution images from low-resolution images while maintaining image quality and reducing data transmission requirements.
Innovation Solution
An electronic apparatus and method utilizing a learning algorithm, specifically information maximizing generative adversarial nets (Infor GAN), to generate high-resolution images from low-resolution images and corresponding characteristic data, enhancing image quality by predicting differences and transmitting additional metadata for improved resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution images are transmitted directly, then image quality is improved, but data transmission requirements increase
Solution Approach 1:
The patent extracts only the essential characteristic data from high-resolution images that is necessary for reconstruction, rather than transmitting the complete high-resolution image data. This selective extraction reduces data transmission requirements while preserving the ability to reconstruct high-quality images at the receiving end.
Solution Approach 2:
The patent performs preliminary processing of images at the transmitting end by generating characteristic data from high-resolution images before transmission. This preliminary action transforms the data into a compressed form that can be efficiently transmitted and later reconstructed into high-resolution images without having to transmit the original large-volume image data.
2Quantity of substance
If low-resolution images are transmitted, then data transmission requirements are reduced, but image quality deteriorates
Solution Approach 1:
The patent introduces characteristic data as an intermediary element between the transmitted low-resolution images and the reconstructed high-resolution images. This characteristic data acts as a mediator that contains essential information needed to transform low-resolution images into high-resolution images through the reconstruction process, thereby maintaining image quality while using low-resolution transmission.
3Manufacturing precision
If complete high-resolution image data is transmitted, then image reconstruction accuracy is improved, but transmission efficiency decreases
Solution Approach 1:
The patent changes the parameter representation of image data by transforming complete high-resolution image data into a different parameter form (characteristic data) that captures essential reconstruction information. This parameter transformation enables accurate image reconstruction while significantly improving transmission efficiency, as the transformed parameters require much less data to be transmitted.
Data Source
AI summary
Disclosed are an electronic apparatus and a method of controlling the same. The electronic apparatus includes: an interface circuitry; and a processor configured to receive a low resolution image for each of a plurality of frames of content and characteristic data from an external apparatus through the interface circuitry, generate, based on the low resolution image and the characteristic data, a high resolution image that has a larger amount of data than the low resolution image and has characteristics corresponding to the characteristic data, and control to display the generated high resolution image on a display.