What can i use better than ORB for matching photos
To handle the issue of lighting variations in your scenario, you can try the following approaches:

Histogram Equalization: Apply histogram equalization to normalize
the lighting conditions of your images. This technique redistributes
the pixel intensities to improve the contrast and make the images
more consistent across different lighting conditions.

Adaptive Thresholding: Instead of using a global threshold for image
binarization, consider using adaptive thresholding techniques. These
methods compute a local threshold for each pixel based on its
neighborhood, which can help handle variations in lighting.

Multi-Scale Analysis: Perform feature detection and matching at
multiple scales to capture different levels of details. By analyzing
the image at different scales, you can mitigate the impact of
lighting variations and improve the chances of finding matching
keypoints.

Image Enhancement Techniques: Apply image enhancement techniques,
such as gamma correction or contrast stretching, to improve the
visibility of details in the images and compensate for lighting
variations.

Explore Deep Learning-based Approaches: Deep learning models, such
as convolutional neural networks (CNNs), have shown promise in
handling variations in lighting conditions. You can consider
training a CNN on your dataset to learn robust features that are
less sensitive to lighting changes.
I have folder named with a lot of location and each of them have 360 degree pics of each of those location i give it a random picture and it has to guess where am i, I tried ORB and it gave me good results and i made it better also but the issue is that lighting conditions might give me a hard time like sunny morning or cloudy morning as per some papers these parameters can cause a issue and i wanted to find is there some way that i can handle this issue is there any way of finding key points irrespective of the weather outside.
I tried to use ORB and getting good results for that movement of time but when lighting changes my dataset is not performing well so i need a solution for that