layout: default title: findHorizon parent: Grid Tools nav_order: 31 —

findHorizon

Description

findHorizon is a specialized image processing utility that performs a transform on a JHC float grid (.r4 file), likely to detect linear or near-linear features (horizons) that exhibit a known curvature. The tool transforms the input image from a standard (x, y) spatial domain into a (roll, y) domain.

The output is a new grid where peaks indicate the presence, vertical position, and “roll” (or tilt) of features in the original image that match the specified curvature. This process is analogous to a slant stack or Radon transform tailored for a specific feature shape, and is likely intended for use with geophysical data like seismic or sidescan sonar profiles where sedimentary layers or other horizons need to be tracked.

Usage 

findHorizon [-curvature <pixels>] [-roll_step <degrees>] <input_floatfile.r4> <output_filterfile.r4>

Arguments

Option Description Default
<input_floatfile.r4> Required. The input JHC-format 32-bit floating-point grid file to be analyzed.  
<output_filterfile.r4> Required. The name for the output transformed .r4 grid file.  
-curvature <pixels> The amplitude, in pixels, of a sinusoidal shape that defines the curvature of the feature being searched for. 20.0
-roll_step <degrees> The angular step size used when testing different tilts or “rolls” for the curved feature. This controls the resolution of the output’s roll axis. 0.1

How It Works

  1. File Opening: Opens the input .r4 grid file and creates the output .r4 file.
  2. Header Reading: Reads the JHC_header from the input file.
  3. Output Grid Setup: Determines the dimensions of the output grid. The Y-dimension will be the same as the input grid (head.dy), while the X-dimension will be determined by roll_step and the range of possible “roll” angles (e.g., -45 to 45 degrees).
  4. Transformation Loop: Iterates through each possible “roll” angle (column in the output grid) and each vertical position (row in the output grid):
    • For each “roll” angle, it constructs a curved integration path across the width of the input image. This path has a sinusoidal shape defined by curvature and roll_angle.
    • It then sums all the pixel values from the input image that lie along this path.
    • This sum becomes a single pixel value in the output grid.
  5. Output Header: Creates a JHC_header for the output file and writes it.
  6. Output Data: Writes the processed float data to the output file.

Output Files

  • <output_filterfile.r4>: A new JHC-format 32-bit floating-point grid file representing the transformed image (roll vs. vertical position).

Dependencies

  • array.h: For JHC_header structure and grid data handling.
  • support.h: For general utility functions and error handling.
  • math.h: For trigonometric functions.

Notes

This tool implements a specialized image transform (similar to a slant stack or Radon transform) that can highlight specific linear features within image data, particularly those with a characteristic curvature. This is useful in applications such as seismic interpretation or geological feature detection. Peaks in the output grid indicate the presence and parameters of such features.

How It Works

For each possible “roll” angle, the tool creates a curved integration path across the width of the input image. This path has a sinusoidal shape defined by the -curvature parameter and is tilted according to the current roll angle. It then sums all the pixel values from the input image that lie along this path. This sum becomes a single pixel value in the output grid.

The output grid’s X-axis represents the “roll” angle, and its Y-axis corresponds to the vertical position (rows) of the input grid. A bright spot at coordinates (roll, y) in the output image signifies that a feature with the defined curvature and a tilt matching roll is likely present at vertical position y in the input image.