Image Processing


Extract & enhance data from your imagery

Image processing software performs calculations that extract and enhance the most important information within a file. This modern, tech-centric approach is usually the first step in computer vision and machine vision as well as pattern recognition systems.

LEADTOOLS & Image Processing at DSCallards

At DSCallards, our team works with LEAD Technologies, the developer and publisher of LEADTOOLS which is an award-winning line of development toolkits.

LEADTOOLS is a family of comprehensive toolkits designed to help programmers integrate raster, document, medical, multimedia, vector and Internet imaging into their applications quickly and easily. The software gives developers the most flexible and powerful imaging technology, offering development support for more than 150 file formats, as well as compression, colour conversion, display and special effects.

Other features include:

  • Scanning/capture
  • Common dialogues
  • Printing
  • Dicom, Pacs & OCR
  • Barcodes
  • Form recognition & PDFs
  • Document clean-up
  • Annotations

For more information about image processing at DSCallards, please contact the team today.

Image Processing

Frequently Asked Questions

What is noise in image processing?

In image processing, noise is the random variation of brightness or colour in an image, frequently appearing as a grainy structure covering the image. Most often caused by degradation in image signals, noise can range from small specks on a digital photograph to more complex optical and radio astronomical imagery that is almost entirely noise and thus requires more sophisticated processing.

What is convolution in image processing?

Convolution is a mathematical practice which is fundamental to image processing. In simple terms, convolution multiplies two arrays of numbers, commonly of different sizes, but of the same dimensionality, to produce a third array of numbers of the same dimensionality.

What is gaussian noise in image processing?

Gaussian Noise, commonly referred to as Gaussian Distribution, is a statistical noise with a probability density function equal to normal distribution. To create this noise, the Image function is combined with a random Gaussian function. Due to the fact that it develops in amplifiers or detectors, it is also known as electronic noise.

What is interpolation in image processing?

Interpolation is a statistical technique which utilises related known variables to predict an unknown price or possible yield of an asset. Interpolation is often carried out by utilising known values that are placed in the same order as the unknown value.

In image processing, interpolation occurs when you resize or distort your image from one-pixel grid to another. At its core, interpolation is a straightforward mathematical idea. One may logically estimate the value of the set at uncalculated points if there is a generally consistent trend throughout a group of data points.

What is quantisation in image processing?

In image processing, quantisation is a compression method used that reduces a range of values to a single quantum value. A stream gets more compressible when the number of discrete symbols in the stream is decreased.

How to process IR images?

At DSCallards, our team work closely with LEAD Technologies, who are the developers and publishers of the award-winning LEADTOOLS software. For more information about how we use LEADTOOLS to process IR imagery, get in touch with us today.

What is image processing?

As the name suggests, image processing in the data analytic sector is the process of transforming an image into a digital form. Image processing is often carried out for the purpose of extracting data.

There are five main types of image processing…

  • Visualisation – Used to locate objects that are not visible in an image.
  • Recognition – Recognition in image processing is used to detect objects in an image and distinguish them.
  • Sharpening and restoration – As the name suggests, sharpening and restoration are used to enhance an image.
  • Pattern recognition – Pattern recognition is used to measure the various patterns around objects in an image.
  • Retrieval – Retrieval is used to browse and search images from a large database of digital images, rather than a single image.

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