Orthorectification is the process of removing the effects of image perspective (tilt) and relief (terrain) from a raw, as-acquired, remote-sensing picture for the purpose of creating a planimetrically correct image. The goal of orthorectification is to create a final, remote-sensing image product wherein every pixel in the image is depicted as if it were viewed at nadir (i.e., directly overhead), thereby removing the distorting effects of the terrain such as hills, valleys, etc. on the data. The key purpose of orthorectification is that once the remote-sensing image has been orthorectified, then geometric computations of distances, areas and directions can be performed more accurately.

These images explain the importance of Orthorectification. Above, distorted road before Orthorectification. Below, planimetrically correct road after Orthorectification
These images explain the importance of Orthorectification. Above, distorted road before Orthorectification. Below, planimetrically correct road after Orthorectification
Orthorectification of Cartosat-1 Satellite data
Orthorectification of Cartosat-1 Satellite data

Today many models and methods of varying complexity exist for orthorectification. At SaraniaSat CANEUS orthorectification is carried out using Bundled Block Adjustment. Bundled Block Adjustment is best understood by examining the individual words in the term. A “bundled” solution for the entire image is computed by including the exterior orientation parameters (the so-called Rational Polynomial Co-efficients (RPCs)) of each image within a small section known as a block using the X, Y, and Z coordinates of tie points (common features between overlapping image sections) and adjusted Ground Control Points (GCPs) that are surveyed independently on the ground using highly accurate Differential GPS (DGPS) techniques. A block of image sections contained within a project is then simultaneously processed to generate a single solution for the entire image. The statistical technique of least squares adjustment is used to estimate the bundled solution for the entire image while also minimizing and distributing error between the individual blocks comprising the image.

Additionally, the use of self-calibrating bundled adjustment (SCBA) techniques in combination with Additional Parameter (AP) modeling accounts for the systematic errors associated with image acquisition camera geometry. Also, the effects of the Earth’s curvature become significant if a large-enough sized photo block or satellite imager is involved. These errors are accounted for during the block triangulation procedure by setting the proper options for the processing.

Methodology employed by SaraniaSat CANEUS: The schematic diagram shown below combined with the description provided describes how we perform Bundled Block Adjustment.

Methodology employed by SaraniaSat CANEUS

Block: Prior to performing any photogrammetric tasks within the Leica Photogrammetry Suite (LPS) Project Manager, an image block must be created. A block is a term used to describe and characterize all the information associated with a photogrammetric mapping project, including:

  • Projection, spheroid and datum information,
  • Imagery used within a project,
  • Camera or sensor model information associated with the imagery,
  • GCPs and their measured image positions and the geometric relationships between the imagery in a project and the ground.


Tie and Control Points: A tie point is a point whose ground coordinates are not known but is visually recognizable within the overlap area between two or more image blocks. The corresponding image positions of tie points for multiple images are identified. Ground coordinates for tie points are subsequently computed during the block triangulation process.

Block Triangulation/ Block Adjustment: Block (or aerial) triangulation is the process of establishing a mathematical relationship between the images contained within a project, the camera or sensor model, and the ground. The information resulting from block triangulation is required as input for the downstream orthorectification, Digital Elevation Model (DEM) creation, and stereo pair creation processes. The term aerial triangulation is commonly used when processing aerial photography and imagery.

Orthorectification-block adjustment using tie points and gcps
Orthorectification-block adjustment using tie points and gcps

The term block triangulation, or simply triangulation, is used when processing satellite imagery. These techniques differ slightly as a function of the types of imagery being processed.


Triangulation: once the images are corrected within the stereo model, then each block is subjected to block triangulation

Block triangulation is conducted over the entire output image and utilizes bundled block adjustment as the functional model to define the relationship between each image pixel and the corresponding ground coordinate.

RMSE Minimization: RMSE stands for Root Mean Square Error, and it is a global indicator of the quality of the orthorectification. The lower the RMSE, the better the Bundled Block Adjustment solution. For example, GCP RMSE is the distance between the input (source) location of a ground control point (GCP) and the retransformed location for the same GCP after the Bundled Block Adjustment process. RMSE is a measure of “fit”, or how closely the retransformed location matches the desired output location of a pixel.

DEM Generation & Editing: SaraniaSat CANEUS has proven experience in DEM editing and generation developed during the delivery of several site suitability assessments for various Hydroelectric projects.

A DEM can sometimes contain pixels with inconsistent or incorrect values. In such cases, the DEM can be edited to smooth out such irregularities to create a more accurate model and, in turn, generate more accurate orthorectified images. For example, pixels within flat areas, such as lakes, often contain misleading elevation values. Applying a constant elevation value to these areas improves the model and produces a more accurate representation of the lake within the ortho image.

Above image shows a 3D anaglyph of several hills and valleys
Orthorectification – 3D anaglyph

Orthorectification - OrthoPhoto Generation
Orthorectification – OrthoPhoto Generation

Orthophoto Generation: Our Orthorectification process involves the use of advanced Rational Polynomial Coefficient functions (RPCs) including block RPC corrections to mitigate the effects of image perspective (tilt) and relief (terrain) and ultimately generate output images that are planimetrically correct and uniformly scaled.

Benefits of Orthorectification

  • Precise Geolocation: As-acquired, unreferenced imagery is subsequently, accurately mapped to the correct geographical coordinates on the earth’s surface.
  • Mosaics: Separate, overlapping images are “stitched’ into seamless, large-area mosaicked images at the desired spatial resolutions.
  • Maximize Efficiency of your operations: SaraniaSat CANEUS eliminates your burden of generating photogrammetrically accurate images.
  • Cost Effective Solutions: SaraniaSat CANEUS’ high-value and cost-efficient photogrammetry core competency significantly reduces your overall project costs.

SaraniaSat CANEUS’ Orthophoto generation services include

  • Multi sensor image fusion
  • Orthorectification and Orthophoto interpretation
  • Color balancing and image mosaicking
  • Object-based image classification

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