diff --git a/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.h b/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.h
index 1b2d80b6d8a..fc27cc359b3 100644
--- a/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.h
+++ b/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.h
@@ -130,45 +130,6 @@ class ITK_TEMPLATE_EXPORT RGBGibbsPriorFilter : public MRFImageFilter<TInputImag
   void
   SetClassifier(typename ClassifierType::Pointer ptrToClassifier);
 
-  /** Set the number of classes. */
-  void
-  SetNumberOfClasses(const unsigned int numberOfClasses) override
-  {
-    itkDebugMacro("setting NumberOfClasses to " << numberOfClasses);
-    if (this->m_NumberOfClasses != numberOfClasses)
-    {
-      this->m_NumberOfClasses = numberOfClasses;
-      this->Modified();
-    }
-  }
-
-  /** Get the number of classes. */
-  [[nodiscard]] unsigned int
-  GetNumberOfClasses() const override
-  {
-    return this->m_NumberOfClasses;
-  }
-
-  /** Set/Get the number of iteration of the Iterated Conditional Mode
-   * (ICM) algorithm. A default value is set at 50 iterations. */
-  void
-  SetMaximumNumberOfIterations(const unsigned int numberOfIterations) override
-  {
-    itkDebugMacro("setting MaximumNumberOfIterations to " << numberOfIterations);
-    if (this->m_MaximumNumberOfIterations != numberOfIterations)
-    {
-      this->m_MaximumNumberOfIterations = numberOfIterations;
-      this->Modified();
-    }
-  }
-
-  /** Get the number of iterations of the Iterated Conditional Mode
-   * (ICM) algorithm. */
-  [[nodiscard]] unsigned int
-  GetMaximumNumberOfIterations() const override
-  {
-    return this->m_MaximumNumberOfIterations;
-  }
 
   /** Set/Get the threshold for the object size. */
   /** @ITKStartGrouping */
@@ -252,12 +213,6 @@ class ITK_TEMPLATE_EXPORT RGBGibbsPriorFilter : public MRFImageFilter<TInputImag
   /** Output. */
   LabelledImageType m_LabelledImage{};
 
-  /** Number of classes that need to be classified. */
-  unsigned int m_NumberOfClasses{ 0 };
-
-  /** Maximum number of iterations. */
-  unsigned int m_MaximumNumberOfIterations{ 10 };
-
   typename ClassifierType::Pointer m_ClassifierPtr{};
 
   /** Threshold for the existence of a boundary. */
diff --git a/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.hxx b/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.hxx
index 5506832f592..27bf180ea35 100644
--- a/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.hxx
+++ b/Modules/Segmentation/MarkovRandomFieldsClassifiers/include/itkRGBGibbsPriorFilter.hxx
@@ -41,6 +41,7 @@ RGBGibbsPriorFilter<TInputImage, TClassifiedImage>::RGBGibbsPriorFilter()
 
 {
   m_StartPoint.Fill(0);
+  this->SetMaximumNumberOfIterations(10);
 }
 
 template <typename TInputImage, typename TClassifiedImage>
@@ -165,7 +166,7 @@ void
 RGBGibbsPriorFilter<TInputImage, TClassifiedImage>::SetClassifier(typename ClassifierType::Pointer ptrToClassifier)
 {
   m_ClassifierPtr = ptrToClassifier;
-  m_ClassifierPtr->SetNumberOfClasses(m_NumberOfClasses);
+  m_ClassifierPtr->SetNumberOfClasses(this->GetNumberOfClasses());
 }
 
 template <typename TInputImage, typename TClassifiedImage>
@@ -683,8 +684,6 @@ RGBGibbsPriorFilter<TInputImage, TClassifiedImage>::PrintSelf(std::ostream & os,
 {
   Superclass::PrintSelf(os, indent);
 
-  os << indent << "NumberOfClasses: " << m_NumberOfClasses << std::endl;
-  os << indent << "MaximumNumberOfIterations: " << m_MaximumNumberOfIterations << std::endl;
   os << indent << "ObjectThreshold: " << m_ObjectThreshold << std::endl;
   os << indent << "BoundaryGradient: " << m_BoundaryGradient << std::endl;
   os << indent << "CliqueWeight_1: " << m_CliqueWeight_1 << std::endl;
diff --git a/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/CMakeLists.txt b/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/CMakeLists.txt
index c5cfc783096..18ec9169c86 100644
--- a/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/CMakeLists.txt
+++ b/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/CMakeLists.txt
@@ -21,3 +21,11 @@ itk_add_test(
     ITKMarkovRandomFieldsClassifiersTestDriver
     itkRGBGibbsPriorFilterTest
 )
+
+set(ITKMarkovRandomFieldsClassifiersGTests itkRGBGibbsPriorFilterGTest.cxx)
+
+creategoogletestdriver(
+  ITKMarkovRandomFieldsClassifiers
+  "${ITKMarkovRandomFieldsClassifiers-Test_LIBRARIES}"
+  "${ITKMarkovRandomFieldsClassifiersGTests}"
+)
diff --git a/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/itkRGBGibbsPriorFilterGTest.cxx b/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/itkRGBGibbsPriorFilterGTest.cxx
new file mode 100644
index 00000000000..5e25be23385
--- /dev/null
+++ b/Modules/Segmentation/MarkovRandomFieldsClassifiers/test/itkRGBGibbsPriorFilterGTest.cxx
@@ -0,0 +1,104 @@
+/*=========================================================================
+ *
+ *  Copyright NumFOCUS
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *         https://www.apache.org/licenses/LICENSE-2.0.txt
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *
+ *=========================================================================*/
+
+#include "itkGTest.h"
+#include "itkMRFImageFilter.h"
+#include "itkRGBGibbsPriorFilter.h"
+#include "itkImage.h"
+#include "itkVector.h"
+
+namespace
+{
+constexpr unsigned int NumberOfBands{ 1 };
+constexpr unsigned int ImageDimension{ 3 };
+using PixelType = itk::Vector<unsigned short, NumberOfBands>;
+using InputImageType = itk::Image<PixelType, ImageDimension>;
+using LabelImageType = itk::Image<unsigned short, ImageDimension>;
+using BaseFilterType = itk::MRFImageFilter<InputImageType, LabelImageType>;
+using GibbsFilterType = itk::RGBGibbsPriorFilter<InputImageType, LabelImageType>;
+} // namespace
+
+TEST(RGBGibbsPriorFilter, DefaultNumberOfClassesIsZero)
+{
+  auto filter = GibbsFilterType::New();
+  EXPECT_EQ(filter->GetNumberOfClasses(), 0u);
+}
+
+TEST(RGBGibbsPriorFilter, DefaultMaximumNumberOfIterationsIsTen)
+{
+  auto filter = GibbsFilterType::New();
+  EXPECT_EQ(filter->GetMaximumNumberOfIterations(), 10u);
+}
+
+TEST(MRFImageFilter, DefaultMaximumNumberOfIterationsIsFifty)
+{
+  auto filter = BaseFilterType::New();
+  EXPECT_EQ(filter->GetMaximumNumberOfIterations(), 50u);
+}
+
+TEST(RGBGibbsPriorFilter, SetGetNumberOfClassesViaSubclass)
+{
+  auto filter = GibbsFilterType::New();
+  filter->SetNumberOfClasses(7u);
+  EXPECT_EQ(filter->GetNumberOfClasses(), 7u);
+}
+
+TEST(RGBGibbsPriorFilter, SetGetMaximumNumberOfIterationsViaSubclass)
+{
+  auto filter = GibbsFilterType::New();
+  filter->SetMaximumNumberOfIterations(25u);
+  EXPECT_EQ(filter->GetMaximumNumberOfIterations(), 25u);
+}
+
+TEST(RGBGibbsPriorFilter, SetGetNumberOfClassesViaBasePointer)
+{
+  auto                   gibbs = GibbsFilterType::New();
+  const BaseFilterType * basePtr = gibbs;
+  BaseFilterType *       baseMutable = gibbs;
+  baseMutable->SetNumberOfClasses(5u);
+  EXPECT_EQ(basePtr->GetNumberOfClasses(), 5u);
+  EXPECT_EQ(gibbs->GetNumberOfClasses(), 5u);
+}
+
+TEST(RGBGibbsPriorFilter, SetGetMaximumNumberOfIterationsViaBasePointer)
+{
+  auto                   gibbs = GibbsFilterType::New();
+  const BaseFilterType * basePtr = gibbs;
+  BaseFilterType *       baseMutable = gibbs;
+  baseMutable->SetMaximumNumberOfIterations(33u);
+  EXPECT_EQ(basePtr->GetMaximumNumberOfIterations(), 33u);
+  EXPECT_EQ(gibbs->GetMaximumNumberOfIterations(), 33u);
+}
+
+TEST(RGBGibbsPriorFilter, ModifiedTimeAdvancesOnNumberOfClassesChange)
+{
+  auto filter = GibbsFilterType::New();
+  filter->SetNumberOfClasses(3u);
+  const auto t1 = filter->GetMTime();
+  filter->SetNumberOfClasses(4u);
+  EXPECT_GT(filter->GetMTime(), t1);
+}
+
+TEST(RGBGibbsPriorFilter, ModifiedTimeUnchangedOnIdenticalAssignment)
+{
+  auto filter = GibbsFilterType::New();
+  filter->SetNumberOfClasses(3u);
+  const auto t1 = filter->GetMTime();
+  filter->SetNumberOfClasses(3u);
+  EXPECT_EQ(filter->GetMTime(), t1);
+}