image_diagnostics#
Purpose#
The image_diagnostics is a node that check the status of the input raw image.
Inner-workings / Algorithms#
Below figure shows the flowchart of image diagnostics node. Each image is divided into small blocks for block state assessment.
Each small image block state is assessed as below figure.
After all image's blocks state are evaluated, the whole image status is summarized as below.
Inputs / Outputs#
Input#
| Name | Type | Description |
|---|---|---|
input/raw_image |
sensor_msgs::msg::Image |
raw image |
Output#
| Name | Type | Description |
|---|---|---|
image_diag/debug/gray_image |
sensor_msgs::msg::Image |
gray image |
image_diag/debug/dft_image |
sensor_msgs::msg::Image |
discrete Fourier transformation image |
image_diag/debug/diag_block_image |
sensor_msgs::msg::Image |
each block state colorization |
image_diag/image_state_diag |
tier4_debug_msgs::msg::Int32Stamped |
image diagnostics status value |
/diagnostics |
diagnostic_msgs::msg::DiagnosticArray |
diagnostics |
Parameters#
Assumptions / Known limits#
- This is proof of concept for image diagnostics and the algorithms still under further improvement.
(Optional) Error detection and handling#
(Optional) Performance characterization#
(Optional) References/External links#
(Optional) Future extensions / Unimplemented parts#
- Consider more specific image distortion/occlusion type, for instance raindrop or dust.
- Consider degraded visibility under fog or rain condition from optical point of view