Local Tone Mapping Logic for Image Signal Processing
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Solution Overview
Problem
Conventional image processing techniques fail to adequately address image distortions and errors introduced by imaging device components, such as defective pixels and lens imperfections, and are often inefficient, leading to loss of image information and artifacts like aliasing and rainbow artifacts.
Innovation Solution
The implementation of local tone mapping logic in an image signal processor that applies a spatially varying local tone curve to image data, preserving local contrast and smoothing intensity differences between pixels, along with other refinements like efficient demosaicing, noise reduction, and geometric distortion correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image processing techniques are used, then processing speed may be maintained, but image quality deteriorates due to loss of image information and introduction of artifacts
Solution Approach 1:
The patent applies parameter changes by using a spatially varying local tone curve with smooth transition parameters. The tone curve parameters are adjusted locally across different regions of the image rather than applying a uniform transformation, allowing preservation of local contrast while avoiding information loss through aggressive global processing.
Solution Approach 2:
The patent implements local quality by applying different tone mapping parameters to different spatial regions of the image. The local tone curve varies smoothly across the image based on local statistics, ensuring that each region is processed according to its specific characteristics rather than a one-size-fits-all approach, thereby preserving image information while improving quality.
2Manufacturing precision
If conventional image processing techniques are used, then processing efficiency may be maintained, but image quality deteriorates due to artifacts like aliasing and rainbow artifacts
Solution Approach 1:
The patent applies local quality by computing local statistics and applying spatially varying tone curves to different regions of the image. This localized processing approach prevents the introduction of global artifacts while preserving local image characteristics, thereby improving image quality without generating aliasing or rainbow artifacts.
Solution Approach 2:
The patent implements dynamics by using adaptive tone mapping parameters that vary dynamically across the image based on local content characteristics. The local tone curve parameters are determined dynamically from local image statistics, allowing the processing to adapt to different regions and avoid static, artifact-prone global transformations.
3Manufacturing precision
If spatially varying local tone curve is applied, then local contrast preservation is improved, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the image into local regions for separate processing. Each region has its own local statistics and tone curve parameters, allowing independent optimization of local contrast preservation. This segmentation approach manages complexity by breaking down the global processing task into manageable local operations.
Solution Approach 2:
The patent uses parameter changes by varying the tone curve parameters locally across different image regions. The local tone mapping parameters are adjusted based on regional characteristics, enabling improved local contrast preservation while the parameter variations are computed efficiently through local statistics rather than complex global optimization.
4Manufacturing precision
If smoothing of local tone curve is applied, then intensity differences between pixels are reduced, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-computing local statistics and determining tone curve parameters before the actual tone mapping operation. The smoothing parameters are established in advance based on local image characteristics, allowing the subsequent tone mapping to proceed efficiently without iterative optimization, thus reducing processing time while maintaining smooth intensity transitions.
Data Source
AI summary
Systems and methods for local tone mapping are provided. In one example, an electronic device includes an electronic display, an imaging device, and an image signal processor. The electronic display may display images of a first bit depth, and the imaging device may include an image sensor that obtains image data of a higher bit depth than the first bit depth. The image signal processor may process the image data, and may include local tone mapping logic that may apply a spatially varying local tone curve to a pixel of the image data to preserve local contrast when displayed on the display. The local tone mapping logic may smooth the local tone curve applied to the intensity difference between the pixel and another nearby pixel exceeds a threshold.