Vignette and Grain Filter Generation for Mobile Image Processing

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Solution Overview

Problem

Current smartphone camera filters lack the ability to efficiently generate and apply spatially varying effects like vignette and grain effects in real-time, limiting their processing efficiency and memory utilization.

Innovation Solution

A method and system that identify vignette or grain parameters in input images using machine learning models, generate corresponding filters or layers, and apply them to other images in real-time, optimizing processor and memory resources for mobile camera hardware.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional camera filters are used for vignette and grain effects, then filter application is possible, but processing efficiency is low and memory utilization is poor

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidmemory utilization

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The filter is divided into two separate components: a vignette filter component and a grain layer component. This segmentation allows each component to be processed and stored independently, improving memory utilization and enabling selective application to reduce overall processing overhead.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The vignette filter and grain layer are pre-generated and stored in memory before being applied to images. This preliminary action eliminates the need for complex real-time calculations during image processing, significantly improving processing efficiency while reducing the computational burden on the device.

Inventive Principle:

Principle #10Preliminary action

2Speed

If real-time filter application is implemented, then processing speed improves, but resource utilization optimization is insufficient

Engineering Contradiction:

Improvereal-time processing speedVSAvoidprocessor and memory resource utilization

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The filter components are generated and stored in advance in memory, allowing for rapid retrieval and application during real-time processing. This eliminates the need for complex on-the-fly calculations, achieving real-time performance while optimizing resource utilization.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The vignette filter and grain layer are created as separate copyable components that can be stored in memory and applied to multiple images without regenerating them. This copying approach reduces processor workload and optimizes memory usage during real-time operations.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS11631202B2System and method for obtaining and applying a vignette filter and grain layer

Publication Date: 2023.04.18 SAMSUNG ELECTRONICS CO LTD

AI summary

A method for generating an image that includes at least one of a vignette effect or a grain effect corresponding to an input image may include obtaining the input image including at least one of the vignette effect or the grain effect; identifying at least one of a vignette parameter or a grain parameter of the input image; obtaining at least one of a vignette filter based on the vignette parameter or a grain layer based on the grain parameter; and generating the image that includes at least one of the vignette effect or the grain effect by applying at least one of the vignette filter or the grain layer to the image.