Signal & Image Processing
Signal and image processing includes the analysis, interpretation, and manipulation of signals. Frequently, the processing must extract or isolate aspects of the signal, or to transform or manipulate it. INNOVARE has particular expertise in the processing of audio/acoustic, speech and image signal processing. The processing itself can take many forms, including.
- Filtering
- Compression
- Feature isolation and extraction
- Enhancement (equalization, noise cancellation, sound removal or addition, etc.)
- Spectrum analysis
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Many industries rely on and benefit from signal and image processing including telecommunications, man / machine communications, medical technology, radar and sonar.
The main applications cover audio signal processing and compressions, digital imaging, video, speech processing and recognition, and digital communications. The use of the science is embedded in products such as mobile telephones, video recorders, high fidelity equipment, multi-media computer equipment, CD players, and televisions. They are used in applications such as weather forecasting, seismic analysis, a wide range of industrial processes, medical imaging like MRIs, sound compression for MP3 audio files, and many more.
Here at Innovare, we work with information intensive industries that require specialized signal or image processing expertise to solve complex business problems. We create the path to a solution for the most complex needs relating to auditory, speech and image signals:
- Isolating likenesses or anomalies
- Identifying important features
- Processing large volumes of data
Why Image & Signal Processing?
Signal or image processing enhances certain features of the data while suppressing others. For instance, in analyzing a fingerprint image against a textured background it may be important to enhance the fingerprint to identify its owner. The appropriate processing would need to focus on features such as the overall texture pattern to be suppressed and the fingerprint's parallel, smoothly curving lines to be enhanced.
Or with an audio signal, it might be important to hear spoken words over the rumble of road noise in a car. In this case, the appropriate processing would focus on suppressing the low frequencies of the rumble and enhancing higher frequencies, particularly just before, at, and just after strong speech-like features such as vowels and loud consonants (like "sh").
Clients typically need these forms of processing when a large quantity of data, such as a long time series, an audio signal, or many images, must be enhanced to reveal important underlying
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