Collage Template Resolution Matching to Prevent Image Blur
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Solution Overview
Problem
Collage images generated by existing video editing applications suffer from blurred images and poor display effects due to the use of fixed resolution settings that result in over-compression of filling images with different resolutions, leading to excessive computational resource usage and terminal operation lag.
Innovation Solution
An image editing method that calculates canvas compression coefficients based on the resolutions of filling images and canvas resolutions to derive a collage image resolution that is less than or equal to the maximum resolution, ensuring optimal clarity and display by dynamically adjusting the compression ratios of each collage canvas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a fixed resolution is set for the collage template, then computational resource overhead is controlled, but image clarity deteriorates due to over-compression of filling images with different resolutions
Solution Approach 1:
The patent applies dynamics by transforming the fixed resolution setting into a dynamic resolution adjustment mechanism. The system calculates compression coefficients based on each filling image's original resolution and the canvas resolution, then dynamically adjusts the derived resolution of the collage template. This allows the resolution to adapt automatically to different input images while controlling computational overhead through the derived resolution calculation.
Solution Approach 2:
The patent changes the resolution parameter dynamically by introducing compression coefficients. Instead of using a single fixed resolution, the system calculates a derived resolution by multiplying the maximum resolution by the compression coefficient, which is determined by the ratio of canvas resolution to original image resolution. This parameter change enables optimal balance between image quality and computational efficiency.
2Loss of energy
If a fixed resolution is set for the collage template, then computational resource overhead is controlled, but display effect deteriorates due to image blur
Solution Approach 1:
The system dynamically adjusts the derived resolution based on the compression coefficient, which varies with each filling image's characteristics. This dynamic adjustment ensures that images are not overly compressed, maintaining display quality and reducing blur, while still controlling computational resources through the derived resolution mechanism.
Solution Approach 2:
By changing the resolution parameter using the compression coefficient formula (derived resolution = maximum resolution × compression coefficient), the system optimizes the balance between computational overhead and display effect. The compression coefficient adapts to each image's original resolution, preventing excessive compression and maintaining visual quality.
3Productivity
If compression ratio is increased to reduce file size, then computational efficiency improves, but image quality deteriorates due to over-compression
Solution Approach 1:
The patent optimizes the compression ratio parameter by calculating it as the ratio of canvas resolution to original image resolution. This dynamic parameter adjustment ensures that images are compressed only to the necessary degree to fit the canvas, avoiding over-compression. The derived resolution then applies this optimized compression ratio to the collage template, balancing computational efficiency with image quality.
4Manufacturing precision
If dynamic resolution adjustment is implemented, then image clarity improves, but device complexity increases
Solution Approach 1:
The patent segments the resolution adjustment process into distinct components: calculating compression coefficients for each filling image, determining the derived resolution based on these coefficients, and applying the derived resolution to the collage template. This segmentation simplifies the implementation of dynamic resolution adjustment by breaking it down into manageable steps, reducing overall system complexity.
Solution Approach 2:
The system performs self-service by automatically calculating compression coefficients and derived resolution without requiring manual intervention. The algorithm autonomously adjusts the resolution based on the input images' characteristics, eliminating the need for complex user interfaces or manual configuration, thereby reducing operational complexity while maintaining image clarity.
Data Source
AI summary
The disclosed embodiments provide an image editing method, apparatus, electronic device and storage medium, which obtains a collage template and corresponding filling images, wherein the collage template represents the layout of at least two collage canvases, and the collage canvases are used to carry the corresponding filling image; obtains canvas compression coefficients of the collage canvases based on the image resolutions of the filling images and the canvas resolutions of the corresponding collage canvases, and the canvas compression coefficients representing the resolution compression ratios of the collage canvases; obtains the derived resolution of the collage template according to the canvas compression coefficients of the collage canvases, and generates a collage image based on the derived resolution.