Defective Pixel Encoding for Image Sensor Memory Reduction
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Solution Overview
Problem
High-resolution image sensors face increased manufacturing costs due to the large memory requirements for storing defective pixel location information, which grows exponentially with the number of pixels, making it difficult to efficiently correct defective pixels in high-resolution cameras.
Innovation Solution
An apparatus and method that losslessly compresses defective pixel information based on the distribution of defective pixels, using a location information encoder and decoder to minimize the size of pixel information stored in memory, allowing for efficient restoration of defective pixels without large storage capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the number of pixels in an image sensor is increased to achieve high-resolution imaging, then the image quality and resolution are improved, but the number of defective pixels increases and the memory capacity required to store defective pixel location information increases exponentially
Solution Approach 1:
The patent divides the sensor panel into multiple scanning regions and processes defective pixel location information in segments during sequential scanning. Instead of storing all defective pixel locations simultaneously, the system processes and stores location data in manageable segments corresponding to different scanning regions, reducing the peak memory capacity required
Solution Approach 2:
The patent transforms the two-dimensional coordinate storage problem into a one-dimensional sequential stream by processing pixels in scanning order. Defective pixel locations are encoded as sequential position information during the scanning process rather than storing full x-y coordinate pairs, effectively reducing the dimensional complexity of data storage
2Reliability
If the capacity of memory is increased to store more defective pixel location information, then more defective pixels can be corrected, but the manufacturing cost of the entire product increases
Solution Approach 1:
The patent extracts only the essential location information needed for defective pixel correction by processing pixels in scanning order and recording only the position of defective pixels relative to the scanning sequence. This selective extraction of necessary information reduces memory requirements and associated manufacturing costs while maintaining correction capability
Solution Approach 2:
The patent changes the representation parameters of defective pixel location data from standard x-y coordinate pairs to sequential position information based on scanning order. This parameter transformation reduces the bit size required to represent each defective pixel location, thereby reducing overall memory capacity needs and manufacturing cost
3Measurement precision
If the bit size of each defective pixel location data is increased to accurately record high-resolution pixel positions, then the location precision is improved, but the total amount of data to be stored increases
Solution Approach 1:
The patent implements a dynamic encoding scheme where the bit size for representing defective pixel positions varies based on the actual distribution and density of defective pixels. Instead of using fixed high-precision coordinates for all pixels, the system adapts the data representation to the specific scanning results, reducing overall data amount while maintaining necessary precision for located defective pixels
Data Source
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AI summary
An apparatus for correcting defective pixels includes an image sensor converting light provided from a subject into an electrical signal and outputting image data, a data memory storing encoded location information, a location information decoder restoring defective pixel location information from the encoded location information stored in the data memory, and a pixel corrector identifying one or more defective pixels from among pixels included in the image data using the defective pixel location information and interpolating the defective pixels using one or more neighboring pixels adjacent to each of the defective pixels.