Added code for preprocessing of YUV images before feeding yuv_to_rgb

tensorflow/python/ops/image_ops_impl.py

@@ -3293,6 +3293,31 @@ def yuv_to_rgb(images):
   The output is only well defined if the Y value in images are in [0,1],
   U and V value are in [-0.5,0.5].
 
+  As per the above description, you need to scale your YUV images if their
+  pixel values are not in the required range. Below given example illustrates
+  preprocessing of each channel of images before feeding them to `yub_to_rgb`.
+
+  ```python
+  yub_images = tf.random.uniform(shape=[100, 64, 64, 3], maxval=255)
+  last_dimension_axis = len(yub_images.shape) - 1
+  yub_tensor_images = tf.truediv(
+      tf.subtract(
+          yub_images,
+          tf.reduce_min(yub_images)
+      ),
+      tf.subtract(
+          tf.reduce_max(yub_images),
+          tf.reduce_min(yub_images)
+       )
+  )
+  y, u, v = tf.split(yub_tensor_images, 3, axis=last_dimension_axis)
+  target_uv_min, target_uv_max = -0.5, 0.5
+  u = u * (target_uv_max - target_uv_min) + target_uv_min
+  v = v * (target_uv_max - target_uv_min) + target_uv_min
+  preprocessed_yub_images = tf.concat([y, u, v], axis=last_dimension_axis)
+  rgb_tensor_images = tf.image.yuv_to_rgb(preprocessed_yub_images)
+  ```
+
   Args:
     images: 2-D or higher rank. Image data to convert. Last dimension must be
       size 3.