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The CEVA Super-Resolution (SR) algorithm increases quality of still images for mobile devices. In today s world, where smartphones are the most commonly used camera devices, image quality is still limited due to slim form factor and strict power constraints. Super-Resolution is an important breakthrough, enabling systems manufacturers and OEMs to increase the quality of images on any device, regardless of these factors. The CEVA SR creates a high resolution, high quality image using multiple consecutive low resolution images. This technique is done using the additional information within the multiple input images in order to increase the details of the output image. The CEVA SR algorithm first handles registration between the input images and then fuses them together into a single, high quality image while supporting ghost removal caused by motion between the consecutive images. Performance Comparison:
SR MethodComplexity [op / pixel]Real-time consideration
Technical PapersMore than 10,000Iterative, high BW
Commercial PC Application100-400
CEVA SR on MM3101Less than 100
Performance: Up to 16 cycles/pixelUtilizes SIMD and specific instructions
The CEVA SR algorithm includes various image enhancement and computational photography algorithmic techniques. It was developed in-house by CEVA s software engineering experts and is optimized specifically for the CEVA-MM3101, utilizing CEVA s advanced Compiler technology and using the CEVA-CV library functions in order to shorten development time.


- Effectively upgrade existing sensors to higher quality ones - Extremely efficient for extending battery life - Allows high-quality digital zoom in real-time - Could be implemented on any device - Supports various number of input images - Supports any image size - Very efficient implementation, able to take multiple shots in single second


- Receive multiple images and fuse them into a single high-resolution image -- For example 5MPixel into 20MPixel image - Ultra low power: <30mW @28nm - Up to 4x resolution increase vs. original picture - No special requirements on the sensor - Configurable software-based solution - Algorithm utilizes parallelism and efficiency of MM3101 architecture and ISA

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