SPATIALIST
SPATIALIST
Take a Step into the Future with Spatial Data
DIGITAL IMAGE PROCESSING
Digital Image processing is a field of study for analyzing and processing digital images. It is used to extract information from or analyze images. This is done by performing various mathematical and algorithmic operations on the images.
Photogrammetry is specifically used to make measurements about the physical world from photographs and to create three-dimensional models. This discipline uses the geometric properties of images to determine the size, shape, position and even movement of objects. Photogrammetry is used in many different fields, especially in land surveying, architecture, archaeology, film and video production, accident analysis and geographic information systems.
Photogrammetry, combined with modern technologies such as high-resolution cameras, laser scanning systems and advanced software, allows us to measure and analyze faster, more efficiently and more accurately. These technological advances will enable photogrammetry to offer an even wider range of applications in the future.
The main link between image processing and photogrammetry is that both work with digital images. Image processing techniques can play an important role in photogrammetric analysis. For example, in a photogrammetric study, image processing methods can be used to reduce noise, improve contrast or emphasize certain features from photographs. These processes can improve the image quality required for accurate measurements and analysis, which is the main goal of photogrammetry.
LiDAR (Light Detection and Ranging) is a technology that uses a laser light to measure the time difference of light reflected from targets and uses this information to determine the three-dimensional position of targets. LiDAR technology is integrated with GPS (Global Positioning System) and IMU (Inertial Measurement Unit) to determine the precise positions of laser measurements. This integration ensures geographically accurate positioning of LiDAR data.
LiDAR's relevance to image processing comes at the stage of processing and analyzing the acquired data. The raw data collected with LiDAR often forms dense and complex data sets. Image processing techniques are used to transform these data into useful and meaningful information. For example, image processing methods such as noise reduction, data filtering, classification and morphological operations can be applied on LiDAR data. Image processing techniques are also used to combine LiDAR data with other imaging techniques. This integration allows for more comprehensive analysis and more detailed inferences.