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Digital Harmonic is a signal and image processing research and development company. The company is headquartered in Ellicott City, Maryland and Scott Haigel is the company's CEO.
Digital Harmonic serves government defense intelligence agencies in providing enhanced signal and image resolution for threat detection and mitigation, and the healthcare industry to reduce radiation dosage requirements for taking medical images. The company also provides commercial businesses with enhanced image and video analysis in oil and gas discovery and engine health monitoring.
The company serves multiple market segments, providing significant upside opportunity for our clients. Digital Harmonic also offers artificial intelligence (AI) and machine learning (ML) solutions by providing dramatically enhanced upstream data for AI and ML algorithms.
Digital Harmonic announces partnering with Dell Technologies to provide its PurePixel technology via edge devices and rack mounted servers to federal agencies on May 13, 2020.
Keyframe is a cross-platform software library that integrates into video workflows to dramatically increase video stream quality and reducing bandwidth. The service delivers lower bandwidth content with zero degradation for end-users. Keyframe enhances video using proprietary algorithms with low latency, enabling encoders to significantly reduce bitrates while achieving better video quality.
PurePixel is a software that performs automatic scene recognition and programmatic manipulation of pixel values to optimize exposure; increase contrast; and detail, deblur and reduce noise in low quality images. The software also helps detect faint anomalies and increase perception of details. When used upstream of a machine learning image classifier, PurePixel can also increase the probability of object classification.
Precision Measure Matrix is a technology developed by Digital Harmonic that utilizes mathematical approaches for measuring signals/waveforms and employs a matrix of multiple simultaneous Fast Fourier Transforms (FFT) to yield extraordinary signal detail in time/frequency/amplitude (TFA).
The matrix delivers 90% fewer measurement anomalies compared to using a single transform and delivers measurable increases in quality of signal processing upstream for improving training sets output results and accuracy.
