image pipelines, compression, and filtering

I'm streaming RGB video from an OAK-D PoE to run an object detector on a GPU, and I'm having some image quality issues. I hope somebody here can shed some light on this for me. We are currently using a different camera for detection. I want to move to the OAK-D, but am having problems with fine scale image texture. Our networks respond strongly to texture, so we have to be careful with image pre-processing.

This image is an example from the other camera. It was saved as H265 video and extracted as a PNG. You can see the texture in the rock face and in the vegetation.

This is an example OAK-D image of the same scene taken at the same time. This was streamed from the camera as H265 video and extracted as PNG. If you zoom in 3x to 5x, you can see that image looks filtered or compressed. We've seen similar things with JPEG compression, and it has caused problems for our network. However, there are so many things to recommend the OAK-D that I want to see if this problem can be solved.

The RGB image pipeline indicates that there are different processing pipelines.

Can somebody tell me the differences among these image types?

Are the artifacts that I'm seeing applied in the "Image Post-Processing" module?

Can I manipulate the way that operates to get the data in the form that I need?

Thanks in advance,
Paul

It was configured for THE_4_K. The code I used is based on the rgb_rull_resolution_saver demo. If it helps, I've pasted it below.

# modified from
# https://docs.luxonis.com/projects/api/en/latest/samples/VideoEncoder/rgb_full_resolution_saver/#demo

import time
from pathlib import Path
import cv2 
import depthai as dai 

# Create pipeline
pipeline = dai.Pipeline()

# Define sources and outputs
camRgb = pipeline.create(dai.node.ColorCamera)
xoutRgb = pipeline.create(dai.node.XLinkOut)
controlIn = pipeline.create(dai.node.XLinkIn)

xoutRgb.setStreamName("rgb")
controlIn.setStreamName("control")

# Properties
camRgb.setBoardSocket(dai.CameraBoardSocket.RGB)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_4_K)

# Linking
camRgb.still.link(xoutRgb.input)
controlIn.out.link(camRgb.inputControl)

# Connect to device and start pipeline
with dai.Device(pipeline) as device:

    # Output queue will be used to get the rgb frames from the output defined above
    qRgb = device.getOutputQueue(name="rgb", maxSize=30, blocking=True)
    controlQueue = device.getInputQueue("control")

    # Make sure the destination path is present before starting to store the examples
    dirName = "data_still"
    Path(dirName).mkdir(parents=True, exist_ok=True)

    start_time = time.time()
    while True:
        inRgb = ( 
            qRgb.tryGet()
        )  # Non-blocking call, will return a new data that has arrived or None otherwise

        if inRgb is not None:
            rgbFrame = inRgb.getCvFrame()
            cv2.imshow("rgb", rgbFrame)
            cv2.imwrite(f"{dirName}/{int(time.time() * 1000)}.png", inRgb.getCvFrame())
            if cv2.waitKey(1) == ord("q"):
                break
        else:
            ctrl = dai.CameraControl()
            ctrl.setCaptureStill(True)
            controlQueue.send(ctrl)
            print(f"The capture mode is {ctrl.getCaptureStill()}")
            time.sleep(0.1)