Add elastic_transform processing for image.py

[shashaka]

I have added the elastic_transform method for NumPy, TensorFlow, Torch, and JAX. If this concept and implementation prove to be effective, I can proceed with adding the ops layer and corresponding test cases.

torchvision's elastic_transform
here is my gist

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 6.93642% with 161 lines in your changes missing coverage. Please review.

Project coverage is 82.19%. Comparing base (0902ff4) to head (db7240b).
Report is 1 commits behind head on master.

Files with missing lines	Patch %	Lines
keras/src/backend/torch/image.py	12.00%	44 Missing ⚠️
keras/src/backend/tensorflow/image.py	4.54%	42 Missing ⚠️
keras/src/backend/numpy/image.py	5.00%	38 Missing ⚠️
keras/src/backend/jax/image.py	5.12%	37 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #20977      +/-   ##
==========================================
- Coverage   82.44%   82.19%   -0.25%     
==========================================
  Files         561      561              
  Lines       53217    53388     +171     
  Branches     8244     8273      +29     
==========================================
+ Hits        43874    43884      +10     
- Misses       7336     7497     +161     
  Partials     2007     2007              

Flag	Coverage Δ
keras	82.01% <6.93%> (-0.25%)	⬇️
keras-jax	63.83% <5.78%> (-0.19%)	⬇️
keras-numpy	58.67% <6.93%> (-0.17%)	⬇️
keras-openvino	32.54% <2.31%> (-0.10%)	⬇️
keras-tensorflow	64.27% <5.78%> (-0.19%)	⬇️
keras-torch	63.88% <5.78%> (-0.20%)	⬇️

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[fchollet]

No fill_mode argument?