Cross-Channel Image Encoding for RGB, Depth, and Alpha Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image encoders lack suitable sample and texture formats to correlate different types of data, such as RGB, alpha, depth, and velocity data, leading to inefficient and inaccurate encoding, high processing time, and resource burden, and are unsuitable for non-Cartesian coordinate systems.
Innovation Solution
An encoder that divides color and other data (alpha, depth, velocity) into blocks and encodes them together, utilizing block coding techniques and transformation methods to enhance accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional encoders encode each data channel separately, then the encoding process is simple, but the processing time increases and computing resources are burdened
Solution Approach 1:
The patent combines multiple data channels (RGB, alpha, depth, velocity) into a unified encoding process. Instead of encoding each channel separately as in conventional encoders, the system merges these different data types into a single integrated encoding workflow, allowing parallel processing and reducing overall processing time while maintaining manageable complexity through structured data organization
2Ease of manufacture
If conventional encoders process data in Cartesian coordinate system only, then the encoding process is straightforward, but the adaptability to different coordinate systems is limited
Solution Approach 1:
The encoder is designed with multi-functional capability to handle multiple coordinate systems (Cartesian, polar, cylindrical, spherical, and custom coordinate systems). The system includes a coordinate system identification module and transformation modules that enable it to automatically detect and adapt to different coordinate systems, making the encoder universally applicable without sacrificing encoding efficiency
Solution Approach 2:
The patent implements dynamic parameter transformation based on the detected coordinate system. When a non-Cartesian coordinate system is identified, the system automatically applies appropriate transformation parameters and algorithms to convert the data into a processable format, allowing the encoder to maintain straightforward processing while adapting to various coordinate systems
3Productivity
If conventional encoders use standard sampling formats, then the encoding is efficient, but the ability to correlate different types of data (RGB, alpha, depth, velocity) is insufficient
Solution Approach 1:
The patent creates a composite data structure that integrates multiple data types (RGB color data, alpha transparency data, depth data, velocity data) into a unified framework. This composite approach allows the encoder to process different data types together with appropriate sampling rates and precision for each type, improving both encoding efficiency through unified processing and data correlation accuracy through integrated structure
Data Source
AI summary
Disclosed is an encoder for encoding images, the encoder having a processor configured to obtain colour data of colour channels of a given image and other data of at least one other channel of the given image, wherein the at least one other channel comprises at least one of: an alpha channel, a depth channel, a velocity channel of the given image; divide the given image into blocks, wherein the colour data and the other data are divided into their own respective blocks; and encode the blocks into encoded data, wherein a given block of the colour data and a corresponding block of the other data are encoded together into the encoded data.